text:
|Publication number
|Publication type
|Application number
|Publication date
|Mar 24, 1992
|Filing date
|Sep 21, 1989
|Priority date
|Sep 21, 1989
|Fee status
|Also published as
|Publication number
|Richard H. Bruce, Alan G. Lewis, Daniel Senderowicz
|Original Assignee
|Xerox Corporation
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (21), Referenced by (35), Classifications (14), Legal Events (7)
|External Links: USPTO, USPTO Assignment, Espacenet
Many measurement or sensing systems require the processing of analogue signals from a large array of detectors. The processing is generally carried out using a digital sub-system, so analogue-to-digital conversion must be performed on the detector outputs.
The analogue-to-digital converter (ADC) must be able to accommodate many simultaneous inputs, and have large throughput. A conventional approach would be to utilize a small number of fast ADCs, each preceded by an analog multiplexer which selects one of the many analog inputs at a time for conversion. However, this technique has limitations; in particular, the analog multiplexing may introduce noise and errors into the analog signals, and the single ADC may be large (an N-bit flash ADC requires 2N comparators and the multiplexing hardware will further increase the chip size) and dissipate significant power in order to meet the speed requirements.
The present invention is a novel ADC system for achieving a high throughput analog-to-digital converter for interfacing analog sensor arrays to a digital system. The system is based on the use of an array of small, low power ADCs and a shift register to transfer the digital data to the output.
Several levels of pipelining are employed in order to increase the effective throughput. The ADC is implemented on a single chip, and has a throughput similar to the throughput of a fast single ADC. However, the invention eliminates the need for analog multiplexing, and the circuit is sufficiently small that input circuits suitable for connecting directly to the sensor array can be included with the ADCs. Thus, the complete interface between an array of analog sensors and a digital signal processor is realized on a single chip.
According to one aspect of the invention, the digital and analog signal paths are separated to reduce noise injection into the analog signals.
According to a further aspect of the invention, a single amplifier is used to charge the ADC capacitors to the analog signal voltage level and to buffer a reference voltage utilized during conversion.
According to a further aspect of the invention, an input integrator is isolated from a charge source during reset and signal transfer to a signal amplifier to prevent the high parasitic capacitance of the array from slowing down the reset and signal transfer operations.
According to a further aspect of the invention, a dual mode input stage is provided to facilitate the conversion of analog charge or voltage signals.
According to a still further aspect of the invention, a unique capacitor array is provided that reduces the chip area required to form the array.
Other features and advantages will be apparent in view of the appended drawings and following detailed description.
FIG. 1 is a block diagram of the system architecture;
FIG. 2A is a schematic diagram of the chip floorplan;
FIG. 2B is a schematic diagram of a typical capacitor array;
FIG. 2C is a schematic diagram of the capacitor array of the present invention; and
FIG. 2D is a schematic diagram of a complete ADC capacitor array;
FIG. 3 is a schematic diagram depicting the analog and digital signal paths;
FIG. 4 is a schematic diagram illustrating pipelining;
FIG. 5 is a schematic diagram of an analog channel;
FIG. 6 is a timing diagram depicting the states of the control signals that control the operation of the analog channel; and
FIG. 7 is a schematic diagram of a comparator; and
FIG. 8 is a schematic diagram of the reference voltage generation and distribution system.
The features that allow integration of a large number of ADCs on a single chip fall into three main areas. First, the design of the analog input circuit and ADC; second, the generation and distribution of bias and reference voltages, and third, the physical layout of the system as a whole. These three aspects of the design are described in detail below. The techniques described are suitable for implementing a large number of ADCs on a single chip, which in this context could be from a few tens to several hundreds. In preferred embodiment, the techniques are demonstrated with 64 integrated ADCs.
To achieve maximum throughput, the design is pipelined. Thus, while an input charge is being integrated (or a voltage sampled), analog-to-digital conversion is being carried out on the previous signal, and at the same time the digital data corresponding to the signal before that is made available at the outputs.
Turning first to the architecture of the system as a whole, FIG. 1 shows the architecture of a Multi-channel Analog-to-Digital Converter (MAD) integrated circuit chip that is a preferred embodiment of the present invention.
In FIG. 1, 64 identical analog channels 10 each consists of an input amplifier 12, which can function either as an integrator with low input impedance for sensing charge from the sensor array or as a switched capacitor buffer with high input impedance for sensing voltage, an intermediate amplifier/reference voltage buffer 14 and an 8-bit successive approximation ADC 16. The digital outputs from the ADC 16 are loaded in parallel into a shift register 18, and subsequently read out serially.
A control logic unit 20 receives externally supplied clock and start and pause synchronization signals, provides control signals to the various analog channels 10 and shift register 18, and an external synchronization signal and pause strobe. The start signal indicates that the system is ready to receive data from an external source and the pause signal allows the system to be temporarily halted without loss of data to facilitate synchronization with slow systems.
The shift register output ports are coupled to an output buffer 22 that drives the signals onto an external bus. On-chip bias generators 23a and b provide bias voltages to the analog channels 10.
The overall architecture illustrated in FIG. 1 has several advantages over the alternative of a multiplexer and single fast ADC. Firstly, the analog signal path is simple and short, minimizing the possibility of signal degradation The multiplexing is carried out by the shift register 18 on digital data, so there is no loss of information. Second, the system of the invention is more efficient in the sense that the individual sub-circuits are able to operate through most of the chip cycle. In a single ADC system, not only would the ADC have to perform 64 conversions, but there would be significant idle time between each conversion while the analog multiplexer settled and transferred its signal to the ADC.
The physical layout of the preferred embodiment is depicted in FIG. 2A. The physical layout of the system is important from two points of view. First, it determines the packing density of the chip; the most important feature in this respect is the structure of the ADC capacitor array described below. Second, the layout has a strong potential influence on the performance of the system, particularly the analog sections, and it is necessary to adopt an appropriate structure for the high level of integration in the MAD chip.
It can be seen that the system contains significant amounts of digital circuitry as well as analog. A major problem with such mixed systems is the injection of noise into the analog sections from the digital. In the preferred embodiment, several features minimize this noise injection. First, the analog sections are contained in well defined regions of the chip, isolated from the digital circuitry by n- and p-type guard bands; this helps minimize the influence of charge injection into the substrate from the digital circuits. Second, separate power supply pads are provided for the analog circuits, digital sections and output buffers, minimizing injection through the supply lines of spurious signals arising from digital switching transients. Third, no digital signals enter the analog sections of the chip except to control the analog switches. Fourth, no analog signal enters the digital sections of the chip.
Each ADC 16 in the analog channel includes an ADC capacitor array is the single largest element in the analog input channel. Thus, minimizing the size of the array is critical to the ability to integrate 64 ADCs on the same chip. The structure of the array utilized in the preferred embodiment is described in detail with reference to FIGS. 2B through 2D.
The capacitors are binary weighted, such that C(ADC2)=2C(ADC1) and so on; thus C(ADC8)=128(ADC1). In order to ensure close matching, all the capacitors are made up of parallel combinations of a minimum capacitor. Thus, 256 such capacitors are required.
Conventionally, polysilicon to diffusion capacitors 80 are laid out as shown in FIG. 2B. An island of polysilicon 81 is entirely surrounded by active area 82, and a small strip 84 is used to connect a polysilicon island 81 to a metal contact 86 on thick oxide. All the capacitors 80 in an ADC array must be laid out in the same way.
In the present chip, an alternative layout is used to reduce the area as depicted in FIG. 2C. In this layout, the capacitance is set by the area of overlap of a polysilicon strip 90 with an active area diffusion 80. By ensuring that the polysilicon strip 90 crosses the diffusion completely, the capacitance is insensitive to alignment errors between the edges of the poly island 81 and the edge of the active area 82 that occur in the layout depicted in FIG. 2B. This allows tighter packing of the capacitors 80, as illustrated in FIG. 2C.
FIG. 2D shows a complete ADC capacitor array using the layout described with reference to FIG. 2C. For simplicity, a 6-bit array is shown, although the area saving with this technique increases with the number of capacitors. Note that very little area is used for wiring between the capacitors 80 since they can often simply be butted together. The wiring is also almost entirely contained within the array without area penalty, and no metal line passes over a capacitor plate to which it is not connected. This technique thus allows a very compact ADC capacitor array to be realized; a similar array laid out conventionally is approximately 60% larger, corresponding to an increase of about 10% in chip area.
FIG. 3 shows a simplified floor plan of the MAD chip illustrating this separation of analog signal path 30, digital data signal path 32, and digital control signal paths 34. The digital signal paths 32 include the connection from the ADC 16 to the shift register 20 and the shift register itself. Note that none of these digital signal paths 32 cross the analog signal paths 30 The input circuits and ADCs are laid out in mirrored pairs (so that each channel 10 is the mirror image of the ones above and bellow it). Thus, a pair of analog signal paths 30a and 30b are controlled by a single digital signal path 30. The digital control lines for controlling the switches in each of the pair 30a and 30b branch from the digital control path 30 thus minimizing the intrusion of digital signals into the analog channel. Further, this feature allows the pair 30a and 30b to share control lines, again saving area.
Turning next to the design of the analog channel 10 and the ADC, each analog channel is pipelined to achieve high throughput.
FIG. 4 is a schematic diagram illustrating the pipeline stages of a single analog channel 10.
An input analog charge signal is received at the beginning of each charge cycle. As is depicted in cycle 1, firstly, a first analog input signal is integrated to form an input voltage signal, secondly, the input capacitor CS1 is charged to the input voltage signal level, thirdly the integrator is reset and the input voltage signal is amplified by the intermediate amplifier to a first amplified voltage level, and finally, the ADC capacitors are charged by the intermediate amplifier to the first amplified voltage level while the external lines are reset. These processing steps are the same for each received analog input signal.
Pipelining is illustrated in cycles 2 and 3. A second analog signal is integrated at the beginning of cycle 2 while the first input voltage signal is converted to a digital representation by the ADC. During this conversion the intermediate amplifier supplies VREFHI to the ADC. The digital representation of the first analog signal is loaded to the digital shift register while CS1 is charged to the second input voltage level. The readout of the digital representation of the first analog input signal via the digital shift register is started at the end of cycle 2 while the second input voltage level is amplified and stored in the ADC.
After two cycles the pipeline is full and three signals are processed each cycle. At the beginning of cycle 3 a third analog charge signal is integrated while the second analog signal is converted and the digital representation of the first analog signal is shifted to the output buffer. A novel feature of this pipeline is the use of the amp 14 both to amplify the input signal to charge the ADC capacitors to the input voltage and as a buffer to provide a reference voltage during the conversion operation.
The input circuit and ADC are replicated 64 times on the system chip. It is thus critical to the ability to achieve this level of integration that each channel be physically small enough, while at the same time maintaining adequate speed for the required throughput and a reasonable power dissipation. The issue of speed is partially dealt with by the pipelined architecture, but a number of other novel features are also necessary as described below.
A simplified schematic of the input circuit and ADC is shown in FIG. 5 and a timing diagram showing the timing of all control signals is depicted in FIG. 6. The switches are in the positions shown in FIG. 5 when the control signals depicted in FIG. 6 are low. All the switches shown are MOS transistors driven by control signals from the Control Logic block 20 shown in FIG. 1.
The first stage of the analog channel 20 is the input integrator 12 which can also be used as a voltage buffer; the mode is simply selected by switch SM. In the voltage sensing mode, switch SV switches one plate of the capacitor Cv between the input and ground; the other plate is connected to the integrator 12 so that the complete input circuit operates as a sample-and-hold device. For charge sensing, switch SM connects the integrator 12 directly to the input pad. The timing of the rest of the circuit is the same in both voltage sensing and charge sensing modes. The charge sensing mode is the most critical for the system, and is described in the rest of this section.
Charge integration is performed in the conventional manner, resulting in a signal voltage at the output of the integrator 12. Once integration is complete, the signal must be transferred to the intermediate amplifier 14 and the integrator 12 reset. However, the integrator input is connected directly to the external sensor and in general there will be a large parasitic capacitance associated with this link. This appears in parallel with the input capacitance of the operational amplifier used in 10 the integrator, and severely slows both the signal transfer to the intermediate amplifier 14 and the reset. The solution to this problem has been to isolate the integrator input from the external sensor for these operations.
Once the charge has been integrated during control clock cycles 0-30 Reset 2 goes low at control clock cycle 30 and SR2 is opened, isolating the integrator 12 from the input. At this stage Store 2 is high and switch SS2 is already closed to provide VREFHI to the right-hand plate of capacitor CS1, and at control clock cycle 30 Store 1 goes high so that SS1 is also closed to the input signal voltage level, i.e., the integrator output voltage, to the left-hand plate of capacitor CS1. Only the intrinsic integrator operational amplifier input capacitance is present to slow this signal transfer.
Once CS1 is charged to the integrator output voltage. Store 2 goes low at control clock cycle 36 to open SS2 and Reset 1 goes high at control clock cycle 37 to close SR1, shorting the integration capacitor and resetting the integrator 12 so that the output voltage of the integrator 12 becomes VREFHI. The charge from CS1 is transferred to CS2, and the magnitude of the output signal of amp 14 is the integrator output voltage multiplied by a gain factor equal to the ratio of CS1/CS2.
Thus, in the analog input circuit it is the output voltage change at the output of the integrator 12 during reset which is amplified rather than the voltage change during integration, although these two are equal and opposite. Once the integrator 12 is reset, Store 1 goes low at control clock cycle 43 to open SS1, separating the amplifier from the integrator; both are then free to perform other operations, achieving the first level of pipelining. In the case of the integrator, SR2 is first closed to reset the input line and SR1 is the opened to integrate the next analog input charge signal. The amplifier charges the ADC capacitor array as discussed below.
The sequence described above has three advantages in addition to preventing high input capacitance from slowing down signal transfer and reset. First, the integrator reset and signal amplification operations are merged, improving throughput and facilitating the pipelined operation. Second, the load seen by the integrator during integration is very small. Third, the amplification takes up a small part of the chip cycle, making the amplifier 14 available to act as a reference voltage buffer for the rest of the chip cycle as described below.
An important aspect of the input circuit and ADC design which allows minimization of area and power dissipation, as well as improved accuracy, is the dual function performed by the intermediate amplifier 14. The amplification operation is described above; the manner in which it is implemented makes it fast, and also limits it to a time when the ADC is dormant, that is during the signal transfer between integrator and amplifier required for pipelining. Thus, the amplifier is available to act as a reference voltage buffer for the Adc during the time when the ADC is active.
During amplification of the signal, when Store 2 is low, the ADC capacitor array is held at VREFLO, that is switches SA0-SA7 are in the left position in FIG. 5. External reset is high so that SC1 is also closed at this time to provide VREFHI to the upper plates of the ADC capacitors. Once amplification is complete Store 1 goes low at control clock cycle 43 to open SS1 and at the same time the entire ADC capacitor array is connected to the amplifier output (SA0-SA7 swing to their right positions) to provide the amplified input signal voltage to the lower plates of the ADC. The capacitor array is thus charged to difference between VREFHI and the amplified input voltage level. At control clock cycle 4 External reset goes low to open SC1 so that the charge induced by the input voltage signal is trapped on the upper plates of the capacitors. Additionally, at control clock cycle 5 Store 2 goes high to reset the amplifier 16 and provide VREFHI to the lower plates of the ADC capacitors. Accordingly, the comparator input voltage level is equal to the sum of the amplified input voltage level and VREFHI and the ADC is ready to start a conventional charge-sharing successive approximation cycle.
In conventional systems, an amplifier for amplifying the input voltage and separate buffers for providing two reference voltages are provided. Thus, at this stage, the capacitors would be switched in turn between the two reference voltages (VREFHI and VREFLO in this case). However, as described above, in the present system SS2 is closed before the ADC cycle starts so that the amplifier 14 acts as a voltage follower, buffering VREFHI.
The use of the intermediate amplifier to fulfill these two requirements (signal amplification and VREFHI buffering) is important for two reasons. First, the need for a separate buffer is eliminated, with obvious savings in area and power consumption; it is estimated that the chip area saving is about 10%, while the power saving is nearly 20%. Secondly, since a common line supplies first the amplified input signal and then VREFHI to the ADC 16, the switches SA0-SA7 need only be two-way devices. In conventional ADCs, a capacity for switching between VREFHI, VREFLO, and the input signal voltage must be provided. This reduced switching requirement of the present system results in an area saving greater that of the eliminated reference buffer alone. Third, since the same amplifier is used to supply the input voltage and VREFH1 to the ADC, its offset is effectively eliminated.
The comparator used in the ADC is shown schematically in FIG. 7. The switch SC1 applies feedback around the first stage only, so there are no stability problems. Since most of the gain is in this stage, offset and flicker noise suppression is not degraded.
An initialization switch, SC2 controlled by an IntRst signal, is included to force the comparator to a condition close to its toggle point just before each decision in the ADC sequence. This speeds the decision, reducing the ADC cycle time and increasing throughput.
Each of the analog input channels 10 described above requires three fixed voltages (in addition to VDD and ground). These are referred to as VBIASO, VREFHI and VREFLO. VBIASO is used by a local bias generator in each channel to set voltages which control the current drawn by each operational amplifier, VREFHI acts as the internal voltage to which all signals are referenced, and VREFLO serves as the voltage defining the gain of the ADC (the gain is actually determined by the difference between VREFHI and VREFLO).
The bias and reference voltages are generated on the chip using band-gap reference circuits. There are major problems associated with generating and distributing the voltages to a large number of channels, each of which presents a significant load. However, on-chip generation does offer a number of advantages, some of which are important in achieving the very high level of analog integration on the system chip.
First, on chip references allow the freedom to choose both the value of the voltages and physical location of the generator. The voltages can thus be chosen for optimum performance of the main analog channels, and the distribution lengths can be minimized. It is also possible to choose the number of channels supplied by a single reference generator. The distribution of an external reference voltage would complicate the chip layout, which is critical for such a dense circuit, and compromise the separation of analog and digital sections as described below. The level of performance required of the analog circuitry also imposes constraints on the acceptable noise level and settling times for the reference voltages, and these can be met more readily using on-chip circuitry. Finally, of course, eliminating external references reduces overall system cost.
The analog circuitry on the system chip is divided into two separate halves, which have no direct communication, as described above. Thus, two separate bias and reference generators 22a and b are required, each supplying 32 channels. In practice, the cost of this is not large; much of the area in the reference sections is taken up by buffers needed to drive the loads presented by the large number of channels each supplies. If a single reference section were used, it would need to be almost as large as the two used in the MAD chip combined in order to drive the greater load.
The VBIASO generator is designed with a small positive temperature coefficient in order to increase the current drawn by the analog circuits as the chip temperature rises. This partially compensates the degradation in channel mobility with temperature, allowing lower power dissipation at room temperature while maintaining acceptable performance at elevated temperatures. The load seen by the VBIASO generator is very light, and a simple unbuffered generator circuit is adequate.
FIG. 8 is a schematic diagram of the reference voltage generation and distribution circuitry. The two reference voltages VREFHI and VREFLO are generated by conventional temperature compensated band gap reference voltage generators 80H and 80L. The generators 80 produce a voltage offset from a reference value indicated by VINIT. In each reference voltage section, a single VREFHI generator 80H is used, referenced to the external ground produces a voltage level of about 3 volts. The output from this voltage generator is sampled when it is valid by two buffers 82A and B, each supplying 16 channels. This keeps the settling time when all the channels sample or inject charge onto the VREFHI line simultaneously acceptable.
The gain of the ADCs is determined by the difference between VREFHI and VREFLO; to keep this as constant as possible, two VREFLO generators are used in each reference section, each referenced to one of the buffered VREFHI lines, to produce a voltage level of about 1.5 volts below VREFHI. The VREFLO signals are buffered and also delivered to 16 channels as shown.
Note that since the buffered VREFHI voltage is supplied to the VINIT input of the VREFLO voltage generator 80L, the offsets of the VREFHI voltage generator 80H and buffer do not effect the magnitude of the difference between VREFHI and VREFLO.
The 64 analog-to-digital converters used in the system chip are of the conventional charge-sharing, successive approximation type except in two main aspects. First, the switching array is simplified by the dual function amplifier/VREFH1 buffer as described above. Secondly, the novel physical capacitor structure is used in the capacitor array in order to minimize its area.
The invention has now been described with reference to a preferred embodiment. Modifications and substitutions will be apparent to a person of skill in the art. Accordingly, the invention is not intended to be limited except as provided by the appended claims.
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|U.S. Classification
|International Classification
|Cooperative Classification
|European Classification
|Sep 21, 1989
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"You want to make sure with a race in which you'll be flying home with other drivers that you don't crash into them. It's happened before, and it can make for a little bit of a tense situation."
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2nd Pennsylvania Regiment
From Wikipedia, the free encyclopedia
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|2nd Pennsylvania Regiment
|Second Continental Congress
|Part of
|Pennsylvania Line
|Pennsylvania Rifle Battalion
|Uniform: blue faced and lined with red, with the letters P S R on the white pewter buttons
|Battle of Long Island (1776)
Battle of Valcour Island (1776)
Battle of Trenton (1776)
Battle of Brandywine (1777)
Battle of Germantown (1777)
Battle of Monmouth (1778)
Battle of Stony Point (1779)
Battle of Springfield (1780)
Battle of Green Spring (1781)
Siege of Yorktown (1781)
|Colonel John Bull
Colonel John Philip De Haas
Colonel James Irvine
Colonel Henry Bicker
Colonel Walter Stewart
The 2nd Pennsylvania Regiment, also known as The 1st Pennsylvania Battalion, was raised, October 12, 1775, under the command of Colonel John Bull for service with the Continental Army. The regiment saw action during the Battles of Brooklyn, Valcour Island, Trenton, the Brandywine, Germantown, Monmouth, and Springfield. The regiment was furloughed June 11, 1783, at Philadelphia, Pennsylvania, and disbanded on November 15, 1783.
- Robert K. Wright, Jr. (1989). The Continental Army. Washington, D.C.: US Army Center of Military History. CMH Pub 60-4.
- Bibliography of the Continental Army in Pennsylvania compiled by the United States Army Center of Military History
- Loane, Paul. 243regiment.com 2nd Pennsylvania Regiment History
|This article about the American Revolutionary War is a stub. You can help Wikipedia by expanding it.


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Compound effects on cloned human Ether-à-go-go related gene (hERG) potassium channels have been used to assess the potential cardiac safety liabilities of drug development candidate compounds. In addition to radioactive ligand displacement tests, two other common approaches are surrogate ion-based flux assays and electrophysiological recordings. The former has much higher throughput, whereas the latter measures directly the effects on ionic currents. Careful characterization in earlier reports has been performed to compare the relative effectiveness of these approaches for known hERG blockers, which often yielded good overall correlation. However, cases were reported showing significant and reproducible differences in potency and/or sensitivity by the two methods. This raises a question concerning the rationale and criteria on which an assay should be selected for evaluating unknown compounds. To provide a general basis for considering assays to profile large compound libraries for hERG activity, we have conducted parallel flux and electrophysiological analyses of 2,000 diverse compounds, representative of the 300,000 compound collection of NIH Molecular Library Small Molecular Repository (MLSMR). Our results indicate that at the conventional testing concentration 1.0μM, the overlap between the two assays ranges from 32% to 50% depending on the hit selection criteria. There was a noticeable rate of false negatives by the thallium-based assay relative to electrophysiological recording, which may be greatly reduced under modified comparative conditions. As these statistical results identify a preferred method for cardiac safety profiling of unknown compounds, they suggest an efficient method combining flux and electrophysiological assays to rapidly profile hERG liabilities of large collection of naive compounds.
Ion channels form a large class of integral membrane proteins. Their malfunction is causal to a variety of human diseases and they represent a class of attractive drug targets.1–3 As a group, they have not been exploited as efficiently as some other target classes, such as proteases and G-protein-coupled receptors.3–5 High-throughput screening (HTS) campaigns designed to identify active compounds for ion channel targets are of great interest, but have met considerable technical challenges.6,7 This limitation is primarily due to the inherent technical challenges associated with measuring electrical currents derived from ion channel activity in HTS formats. Currents passing through ion channels are often small and transient and require special conditions to activate, all of which can pose challenges for HTS implementation. In recent years, the rapid progress in developing functional assays and instrumentation has enabled HTS campaigns on an expanding variety of channel types.6,8
Ion channels are functionally diverse and exhibit a variety of properties critical for their physiological roles, most prominently their ability to allow selective permeation of ions. The major classes of channels can be defined based on ion permeation of potassium, sodium, calcium, chloride, or a mixture of these ions. Ionic selectivity is a key determinant of physiological function and an important factor in HTS assays' design and performance. Functional cell-based assays tend to yield a more physiological readout than some nonfunctional biochemical assays and are thus increasingly used in HTS ion channel assays.9 The two major types of nonelectrophysiological functional assays implemented using current technologies are based on detecting either the change of concentration of the permeated ions (or their surrogates) or the consequence of the concentration change. The former is usually carried out by taking advantage of fluorescent dyes that selectively bind to the targeted ions.8,10,11 The latter is often based on the membrane potential changes following ion fluxes.12,13 Using surrogate ionic fluxes, several large HTS campaigns have been recently described in published reports14,15 and in a public database (PubChem AIDs 1456, 1511, 1672, 1918, 2156, and 2239). Examples of HTS campaigns using direct measurement of ionic current have been less commonly reported.16
Voltage-gated potassium channels are an important class of drug targets.17 Modulators of these channels have been reported,17,18 some of which were identified via HTS compound screens using flux-based assays.19–21 The primary approach has involved the use of surrogate ions such as rubidium (Rb+) or thallium (Tl+), which may be detected by atomic absorption spectrometry22,23 or fluorescent dyes.8,10,11 With the advent of automated patch-clamps,6,24–27 it is now possible to consider whether the more direct measurements of channel electrophysiological activity obtained from the automated patch-clamp justifies its higher implementation cost in high-throughput screens. It is therefore important to obtain more specific and quantitative information to assess the cost and benefit comparatives between assays employing electrophysiological methods versus surrogate ion flux measurements.
Promiscuous block of the cardiac potassium channel encoded by human Ether-à-go-go related gene (hERG) is a major cause of cardiac toxicity by a variety of clinical drugs. Both flux assay and electrophysiological approaches have been applied to determine the potential cardiac toxicity risk of the developing compounds.16,28 We therefore used hERG as the testing channel and performed comparative analyses of Tl+-based flux assays and electrophysiological recording of a voltage-gated potassium channel. Our experiments employed a validation set (~2,000 compounds) representative of the NIH Molecular Library Small Molecular Repository (MLSMR), which consists of more than 300,000 compounds and has been used in all screens of the molecular library initiative (http://mli.nih.gov/mli/). Therefore, the reported experiments favor a screening collection of diverse compounds instead of a drug-like collection. The hERG Tl+ assay was optimized to identify inhibitors (PubChem AID 1511). The electrophysiological assay used population-based recording methods and was designed to allow identification of both inhibitors and potentiators. The described assay conditions are comparable to what has been reported by others, as judged by IC50 values.11,29 The resultant hits from these screens under different selective criteria were analyzed and compared to assess these two assays. This approach differs from previously published analyses of hERG assays in which comparison of IC50 values of mostly known hERG blockers was performed to identify the preferred approach for safety evaluation and compound optimization. The present study employs a statistical approach to compare different HTS assays to quickly assess the effectiveness of assays to be employed for evaluation of hERG liabilities of large sets of compounds.
A stable cell line expressing hERG was previously generated using Chinese hamster ovary cells. These cells were routinely cultured in complete Dulbecco's modified Eagle's medium/nutrient mixture F-12 medium (Mediatech, Herndon, VA) supplemented with 10% fetal bovine serum (Gemini, Calabasas, CA), 2mM l-glutamine (Invitrogen, Carlsbad, CA), and 500μg/mL G418 (Invitrogen). They were cultured at 37°C under 5% CO2. Cells were maintained and passaged till 80% confluence was reached.
The validation set of the MLSMR library, including 1,999 test compounds of various structures, was selected for the flux and electrophysiological assays. To determine whether the MLSMR validation set defines a more structurally representative subset of the larger MLSMR library than other possible small-molecule validation sets, we computed the number of structural neighbors in the entire MLSMR library for each compound in (1) the MLSMR validation set of 1,999 compounds (Biofocus DPI, San Francisco, CA) and (2) the Library of Pharmacologically Active Compounds (LOPAC) collection of 1,280 compounds (Sigma, St. Louis, MO), as well as the number of total unique structural neighbors in the MLSMR library for each set. We also performed these calculations for 100 random samples of MLSMR library subsets of size 1,000, 2,000, 3,000, 4,000, and 5,000 compounds. Finally, we performed a greedy optimization to estimate the subset with the maximal number of unique structural neighbors for a given compound subset size. This greedy approach used the standard algorithm for problems such as vertex cover: iterative selection of the compound with the greatest number of neighbors that are not neighbors of previously selected compounds. For these calculations, we computed ECFP_4 circular fingerprints hashed to binary strings of length 1,024 for each compound using Pipeline Pilot 188.8.131.52 Student Edition (Accelrys, San Diego, CA). Circular fingerprints measure structural patterns present in radial bond neighborhoods surrounding each nonhydrogen atom in a small molecule and have been previously demonstrated to contain high information content relative to other 2D structural descriptors.30–32 Because these descriptors sample an immense feature space of possible atom bond neighborhoods, they are hashed into binary strings of length suitable for computation. For each compound set, we removed fragments, standardized both coordinates and charges using Pipeline Pilot, and removed duplicate compound records (as determined by comparison of canonical SMILES strings computed in Pipeline Pilot). For each compound in the MLSMR validation set, LOPAC collection, and the whole library, we computed the Tanimoto coefficient with every compound in the MLSMR library:
where A and B are the number of "on" bits in compounds i and j. Thus, each compound receives a score between 1 and 0 representing its similarity to a compound in the MLSMR library. Collections of compounds in the MLSMR library were judged similar to compounds in the validation set or LOPAC collection if their Tanimoto coefficient was greater than 0.3 or 0.7 compared with the target. The 0.3 threshold value has been previously observed as being the lowest score to correlate with the degree of structural similarity at which similar biological activity of small molecules may be expected.33,34 The 0.7 threshold value has been commonly used because it gives much higher confidence in correlating structural similarity. Theoretically, a Tanimoto coefficient of 1 should represent structurally identical compounds. However, because of the hashing step necessary to calculate binary fingerprints, we have observed in practice that sometimes nonidentical compounds may be assigned a Tanimoto coefficient of 1. Therefore, we set an upper limit on similarity between compounds in the validation set and LOPAC compared with the MLSMR library to be 1. To remove any comparisons of compounds to themselves, we subtracted 1 from the number of nearest neighbors for each compound in the validation set, and 1 from the number of nearest neighbors for those LOPAC compounds present in the MLSMR library (498/1,264 compounds). Random MLSMR subset selection and the greedy optimization algorithm were performed using in-house programs written in C++. Statistical analysis on the final datasets was performed with MATLAB (Mathworks, Natick, MA).
The validation compounds from BioFocus Discovery Partners International (Biofocus DPI) were dissolved in dimethyl sulfoxide (DMSO) with a concentration of 5mM in 384-well polystyrene plates. All compounds are of >90% purity, as determined by liquid chromatography–mass spectrometry. They were diluted to the test concentration on the day of the experiments. The test compounds were examined at 1 and 10μM in Tl+-based flux assays and at 1μM for electrophysiological assays. The control compound, dofetilide (N-[4-[2-[2-[4-(methanesulfonamido)phenoxy]ethyl-methylamino]ethyl]phenyl] methane sulfonamide) (Fisher Scientific, Pittsburg, PA) was dissolved in DMSO at a concentration of 20mM.
Activity of potassium channels was monitored by the influx of a surrogate ion, Tl+, for potassium. Tl+ influx was detected through the use of a Tl+-sensitive fluorescent dye, FluxOR™ (Invitrogen). Cells were seeded at 6,500 cells per well into BD Biocoat poly-d-lysine–coated 384-well plates using a Multidrop (Thermo Scientific, Hudson, NH) and incubated overnight at 37°C under 5% CO2. The Tl+-based fluorescence assay protocol (see Appendix) was adapted from the manufacturer's recommended protocol. Briefly, medium was removed; cells were incubated with 1× FluxOR solution, 25μL/well, for 90min at room temperature in the dark; the 1× FluxOR solution was replaced by assay buffer (Hanks balanced salt solution containing 5.8mM potassium; Catalog No. 14065; Invitrogen), 20μL/well; 7.5× test compounds and controls in assay buffer were then added to cells, 4μL/well; 20min later, cell plates were loaded to Hamamatsu FDSS 6000 kinetic imaging plate reader (Hamamatsu Photonics, Hamamatsu, Japan); after establishing fluorescence baseline by 1Hz scanning for 10s, the hERG channels were activated by addition of 6μL/well stimulus buffer containing 25mM K2SO4 and 7mM Tl2SO4 to the assay buffer, giving a final potassium concentration of 15.8mM and final Tl+ concentration of 2.8mM; and fluorescence measurement was continued at 1Hz for another 110s. To evaluate the robustness of the HTS Tl+-based fluorescence assays, dofetilide at 1μM was applied as positive control, whereas assay buffer was employed as negative control. Both the positive and negative controls were prepared with either 0.02% (v/v) or 0.2% (v/v) DMSO, corresponding to 1 and 10μM test concentrations, respectively. The fluorescence ratio, F(max–min)/F0 (ΔF/F0), was calculated for each well using the entire 120s detection window and then normalized to the positive and negative control wells. Compared with the negative controls, if a compound caused signal decrease by more than three times the standard deviation (SD) in fluorescence ratio, it was classified an inhibitor.
Automated patch-clamp experiments were performed using the population patch-clamp mode of automated voltage clamp recording with IonWorks Quattro™ (Molecular Devices Corporation, Sunnyvale, CA). Briefly, compound effects on the hERG channel were tested at 1μM with a two-step voltage protocol. The Chinese hamster ovary cells stably expressing hERG channels were dislodged from flasks and dispensed into a 384-well population patch-clamp mode plate. After dispensing, seal resistance of cells was measured for each well and cells were perforated by incubation with 100μg/mL amphotericin B (Sigma). Activity of hERG was then measured with the recording protocol as follows: cells were held at −70mV, stepped down to −80mV for 100ms to estimate leak currents, and depolarized to −30mV for 100ms to estimate non-hERG currents. Then, hERG currents were evoked by two voltage pulses with a 20mV difference at the depolarization steps. During the first pulse, cells were depolarized to +20mV for 2s and hyperpolarized to −30mV for 2s. Prior to the second pulse, cells were held at −70mV for 3s. Then cells were depolarized to +40mV for 2s followed by a hyperpolarization to −30mV for 2s. This series of pulses was applied to cells before and following a 3-min incubation of cells with 1μM test compounds or assay buffer. Positive (1μM dofetilide) and negative controls (external buffer with 0.02% [v/v] DMSO) were applied within each plate to evaluate the data quality. Only cells with a tail current amplitude bigger than 0.2nA, a seal resistance >30MOhms, and seal resistance drop rate lower than 25% were included for data analysis. The peak amplitudes of tail currents before and after compound treatment were measured. Compound effects were assessed by the percentage change in the hERG tail current. The percentage changes were calculated by dividing the difference between pre- and post-compound hERG tail currents by the respective pre-compound tail current in the same well and normalized to positive and negative controls in the same plate. Compared with the negative controls, if a compound decreased the hERG tail current by >3 SD, it was classified as an inhibitor.
Whole-cell currents were measured in the following recording buffers: 137mM NaCl, 4mM KCl, 1mM MgCl2, 1.8mM CaCl2, 10mM HEPES, and 10mM glucose, pH 7.4 adjusted with NaOH (extracellular solution); 40mM KCl, 100mM K-gluconate, 1mM MgCl2, and 5mM HEPES, pH 7.2 adjusted with KOH (intracellular solution). The voltages listed above were before correction for liquid junction potential. An online correction of −20mV was applied to correct for junction potentials. The current signal was sampled at 0.625kHz.
The data from the Tl+-based flux assay were analyzed by the manufacturer's software package (Hamamatsu Photonics) and the automated patch-clamp experiments were analyzed in IonWorks 126.96.36.199 (Molecular Devices Corporation). Further calculations were performed in Excel (Microsoft, CA). Linear correlation and graphic plots were carried out in Origin 7.0 (OriginLab Corporation, Northampton, MA) and Spotfire (TIBCO, Somerville, MA).
To evaluate the extent of correlation between the Tl+-based flux assay and the population patch-based electrophysiological assay, we selected a validation set of 1,999 compounds. This group of compounds was assembled as a representation of the ~300,000 MLSMR compound library (http://mlsmr.glpg.com/MLSMR_HomePage/). We use this collection to help gauge how different assays may perform if the entire MLSMR was to be tested.
To obtain a more quantitative assessment, we computed ECFP_4 circular fingerprints hashed to binary strings of length 1,024 for each compound (see Materials and Methods section). The number of neighbor compounds existing in the MLSMR library was higher for most compounds in the validation set compared with the LOPAC collection (Fig. 1A). The mean and standard error for the number of structural neighbors for the individual compounds in each set was, respectively, 829.5±27.8 (validation set) and 306.7±18.6 (LOPAC) if a 0.3 Tanimoto coefficient threshold is applied (Fig. 1A). When applying a 0.7 threshold, the value for LOPAC collection was close to zero (data not shown), consistent with the notion that more compounds in LOPAC are bioactive and unique relative to the validation set. We compared this to random samples of 100 of subsets of size 1,000, 2,000, 3,000, 4,000, and 5,000 of the MLSMR collection, which suggested that both the validation and LOPAC compound sets had lower numbers of individual neighbors per compound than random subsets of the library (Fig. 1A): the mean and standard error for the number of neighbors per compound for the entire library is 1,618±31, suggesting that the values obtained for the random subsets are representative of the statistics of the library as a whole. Because compounds within a given collection may share the same neighbors, we also compared the number of unique neighbors in the MLSMR library for all compounds in the validation and LOPAC collections to both 100 random samples of subsets of size 1,000, 2,000, 3,000, 4,000, and 5,000 of the library, and a greedy optimization for maximum coverage (Fig. 1B). The results follow a similar trend to the calculations for number of neighbors per individual compounds. It should be noted that the validation set, although structurally more similar to the MLSMR library than the LOPAC collection using either a 0.3 or 0.7 threshold, actually appears to cover less of the collection with its structural neighbors than random MLSMR subsets (Fig. 1B). Because the MLSMR library contains products of combinatorial chemistry (Fig. 1D, Diversity compounds), in which a single scaffold is extensively augmented with diverse R groups, many compounds will have a large number of structural neighbors that are analogs in their respective combinatorial synthesis families. Conversely, subsets such as the validation compounds, which are more biased toward known bioactive compounds, may exclude such diversity compounds (Fig. 1D) and thus have an overall smaller number of unique neighbors. However, a recent study has suggested that the biologically active domain of chemical space is better covered by a relatively small set of natural-product-like compounds than a larger set of combinatorial compounds representing extensive structural diversity.6 Thus, although the validation set has an overall lesser number of unique neighbors in the MLSMR library than random subsets, it represents a mixture of diversity compounds and bioactives. Comparing only the LOPAC and validation sets, the number of structural neighbors per compound in the MLSMR library for the validation and LOPAC collections was significantly different as assessed by a two-sample t-test (P=3.2603 e−042) (Fig. 1C). Our analysis provides a quantitative basis that the validation set is, on a whole, more structurally representative of the chemical space spanned by the entire MLSMR library than the LOPAC collection. In addition, the results could allow us to examine whether bioactives and diversity compounds within the validation set display any collective difference.
HTS campaigns including Tl+ and other flux-based assays are often performed using single concentrations of 1–20μM. To gain additional information concerning the dynamic window, we performed our hERG assays at both 1 and 10μM. An additional reason for including 1μM drug concentration is that this concentration may be used to evaluate hERG-caused cardiotoxicity.35,36 The hERG Tl+-based assay was performed in duplicate at both concentrations to evaluate fidelity over a wider dynamic range and the results are plotted in Figure 2. Figures 2A and 2B show linear regression plots of two repeats for 1 and 10μM concentrations as indicated. The R2 values were 0.974 and 0.972, respectively. This degree of convergence for data obtained at 1 and 10μM suggests that this assay format may be used to identify hERG inhibitors with IC50 values less than or equal to the test concentrations. The control measurements made on each test plate were included in the data shown in Figure 2A and 2B. Analysis of variation in the normalized buffer control values was used to calculate criteria for hit identification as shown in Figure 2C, in which the dashed lines represent ±3 SD of the buffer control measurements and are plotted along with values obtained for test compounds. With this threshold, a total of 467 hits were identified at 1μM test concentration and, as expected, more compounds (1,111) were identified as hits at 10μM. Approximately 23% of compounds tested at 1μM were active as inhibitors at the −3 SD level and 56% were active when tested at 10μM (Table 1). This result is consistent with existing reports by others that the Tl+ assay is less sensitive than the electrophysiological assay.11,29 To assess the reliability of the hit selection process, we calculated the fraction of hits identified at 1μM that were also identified as hits at 10μM, which indicate that 94% (440/467) of the 1μM hits confirmed at 10μM. This suggests that this approach may be useful for large-scale classification of chemotypes. This hit rate is significantly higher than the expected rate of false positives expected for a normally distributed population. It is consistent with the existing data that a variety of chemotypes block hERG channels.36,37
Electrophysiological tests for hERG were carried out using the population patch recording mode on IonWorks Quattro (see Materials and Methods section). The promiscuous inhibition of hERG channels by a variety of chemical structures36,38 and the high hit rate for hERG inhibitors observed in the Tl+ assay favor the idea of focusing the analyses of effects in the IonWorks assay to data obtained at 1μM compound concentration. The duplicate tests of 1,999 compounds yielded 1,373 pairs of data points from two repeats of separate plates, representing an average of 86% success rate of electrophysiological recording per plate. Failure of some compounds in electrophysiological tests may have resulted from specific chemical effects on cell health and seal quality. To explore this possibility, these compounds were analyzed for unique chemical properties that might be common to failed compounds, such as molecular weight, solubility, and hydrophobicity (ClogP). We did not detect any convincing pattern of shared properties for these failed compounds. Hence, the fluctuation of data quality was likely caused primarily by batch-to-batch cell variability, channel-dependent characteristics, and/or instrument stability.
Good agreement between replicates in the IonWorks assay was observed (R2=0.872) with a slope of 1 (Fig. 3A), suggesting the assay is sufficiently fit for reliable hit identification. Based on the high correlation coefficient between replicate tests, the hit selection process was applied to the set of 1,927 compounds for which one or two determinations were made. Application of a hit selection criterion of −3 SD for inhibitors, same as was used for Tl+ assay, has identified a total of 373 hits, yielding a 19% hit rate (Fig. 3B and Table 1).
The correlation between block of hERG tail currents in the electrophysiological assay and block of Tl+ influx in the fluorescent assay is plotted in Figure 4A for the 1,927 compounds for which both data types exist. A moderate positive correlation was observed (R2=0.609), with a significant number of compounds falling outside the predicted 95% confidence limits (dashed lines). Among the combined total of 638 hits identified by Tl+ and electrophysiological assays as hits (larger than −3 SD of buffer) at 1μM test concentration, only 202 compounds were picked up by both assays, yielding ~32% overlap (Table 1). Because the electrophysiological method directly measures ionic current, the false negatives identified by the Tl+ assay are of concern. We retested some of these compounds individually and confirmed their inhibitory effects. Figure 4B displays the structure of pyrilamine (CID 5284451) with potent inhibition of hERG currents (Fig. 4D). In contrast, it failed to significantly block Tl+ flux in the fluorescent assay over the entire 120-s recording period at 1μM (Fig. 4C). The IC50 value of pyrilamine is 1.67±0.04μM by electrophysiological recording, but it is well above 10μM in the Tl+ assay (data not shown). Pyrilamine is a previously known hERG blocker39 and has no detectable fluorescence that may cause interference to the Tl+-based measurement.
Indeed, the degree of overlap between the assay results is a key parameter to gauge the effectiveness of the Tl+-based assay. To evaluate whether there are shared properties among the compounds positive in the Tl+ assay but not detectable in the electrophysiological assay, we analyzed their physical and chemical properties. There was no detectable trend (Supplementary Figs. S1 and S2; Supplementary Data are available online at www.liebertonline.com/adt). We further analyzed the data by comparing hit overlaps using different hit selection criteria for the two assays. Specifically, we examined how the threshold of hit selection might reduce the number of false negatives. We first plotted the percentage of hits by the electrophysiological assay that is selected by the Tl+-based assay. Using the data from 1μM concentration for both assays, 58%–71% of IonWorks hits were identified using 1–5 SD selection criteria in the Tl+ assay (Fig. 5A). When similar analyses were performed using the data from the electrophysiological assay at 1μM compared with data from the Tl+-based assay obtained at 10μM, there is a noticeable improvement in the percentage of IonWorks hits identified, ranging from 79% to 90% coverage depending on hit selection criteria. However, the overlap of hits between the two assays was not improved by comparing the IonWorks data at 1μM with the Tl+ data at 10μM (Fig. 5B and Table 1).
Using flux of surrogate ions to assess ion channel activity has dramatically improved the throughput of cell-based assays for ion channels. This approach is particularly useful when considering its general applicability to an entire class of ion channels, for instance, using Tl+ or Rb+ fluxes to assess potassium channel function. This method for detecting ion channel activity can be coupled with various approaches for triggering or modulating channel activity so that assays for channels with different modes of channel gating can be established in high-throughput formats. An ongoing concern when implementing high-throughput ion channel assays using surrogate ion flux to track channel activity is the ability of an assay to reliably monitor ion channel fluxes in a more physiological context. Electrophysiological measurements of ion channel activity are often performed under restrictive or nonphysiological conditions, but are still the most accessible current methods used to directly measure ion channel activity under conditions that may generate relevant pharmacological data.
The data in this report reveal 32% overlap between hits identified by a Tl+-based surrogate ion assay and those identified by automated patch-clamp recordings using criteria that defined inhibitory hits as signal values lower than −3 SD of the buffer control values on each plate. Although it is recognized that the SD values for different assays were different, the degree of hit overlap between the assays did not improve as the criteria for hit selection was increased to larger than −5 SD. Indeed, this modest level of overlap is surprising. A few factors may contribute to this lower than expected level. First, it is well known that the surrogate ions have considerably different permeabilities from that of physiologic ions. This has been proposed to contribute to a right shift of IC50 values for known compounds inhibiting hERG potassium channels.40 In this case, using a higher concentration of testing compounds may yield a better overlap of hits identified by two different assays. Analysis of the Tl+ assay hits identified at 10μM testing compound concentration (Table 1 and Supplementary Fig. S3) revealed that, as expected, more hits were identified at each selection criteria compared with 1μM testing, and fewer Tl+-negative/IonWorks-positive compounds were identified. However, this approach did not increase the overlap between the Tl+ assay hits and the IonWorks hits because of large increases in the numbers of Tl+-positive/IonWorks-negative compounds.
Second, based on studies using known inhibitors of hERG potassium channels, it is clear that different compounds display varying degrees of right shift of potency, as large as 100-fold, in surrogate ion-based flux assays.40 Therefore, the structural features of testing compounds may differentially affect the inhibitory potency in each assay. This factor may be especially more pronounced for hERG than for other channels because hERG is inhibited by a variety of structural classes. Indeed, the Tl-based assay may be further optimized to improve its correlation with electrophysiological recording. Under our assay conditions, IC50 values of dofetilide and terfenadine, two structurally distinct hERG inhibitors, have different degrees of affinity shift when tested in two assays. Based on the Tl+-based assay, their IC50 values are 35.3±1.3 and 1,256.6±77.1nM. These values are similar to those reported in literature, for example, 26 and 1,278nM by Bridal et al.29 Both ours and the earlier reports have shown different degrees of right-shift of dose–response curve depending on the given compound tested. It is conceivable that further optimization of the Tl+-based flux assay could yield a better correlation with electrophysiology, hence arguing for the need of channel-specific assay optimization.
Third, many ion channels display distinct gating characteristics in response to different physiological conditions. For hERG channels, the rapid and precise voltage protocol applied by the automated patch-clamp used to isolate tail currents has considerably higher resolution that is unattainable by a change of extracellular ion concentration introduced via liquid handling, which is commonly used for triggering channel opening in flux assays. As a result, the flux assay, although target specific, may not replicate gating-specific pharmacological effects measured in patch-clamp studies. Of course, the degree of correlation between different assay formats may depend on the target and the properties of active compounds sought by the primary screen.
The present study examines the correlations between compounds inhibiting hERG channels in a fluorescent Tl+ influx assay and an electrophysiological assay performed on an IonWorks 384-well automated patch-clamp instrument. A structurally diverse set of 1,999 compounds assembled from the NIH MLSMR library was used to examine these assays in an HTS format. The validation set contains both diverse compounds and bioactives. With the −3 SD criteria, the hit rate for non-"known bioactives" in the Tl+ assay is 23.3% at 1μM and 54.9% at 10μM. The hit rate for "known-bioactives" in the Tl+ assay is 23.4% at 1μM and 56.9% at 10μM. In the electrophysiology assay, the hit rate for naïve compounds is 20.4% and 17.2% for known bioactives. Although the validation set does not perfectly represent the MLSMR collection, its diversity compounds and known bioactives show similar performance in the two assays. One may speculate that the naive diversity compounds in MLSMR have uncharacterized bioactivity against hERG. Additionally, because there are considerable data obtained with the validation set available in PubChem, our results may be further analyzed in the context of other assays and targets.
The purpose of these experiments is not to determine the preferred or most reliable predictor of hERG liabilities for cardiac safety screening. That question has been addressed in a number of publications using IC50 values calculated from small sets of compounds typically with defined hERG-blocking properties (e.g., refs.11,29). The data presented here provide more relevant argument for the importance of electrophysiological assays using statistical data from a much larger collection of naïve compounds. The present experiments indicate that the hERG Tl+ flux assay used in the present format can be used to classify hERG-inhibitory properties of large sets of compounds. A significant fraction (1/4) of the combined hit set was negative in the flux assay and positive in the IonWorks assay when tested at 1μM in both assays. This fraction decreased to 1/10 when comparing the flux assay results obtained at 10μM with the IonWorks data at 1μM. Therefore, a workflow utilizing a Tl+ flux high-density assay at a higher testing concentration followed by electrophysiological recording to validate the active compounds may remain an effective approach for rapid and efficient characterization of hERG inhibitory properties of large sets of compounds. Alternative approaches with lower numbers of false negatives and false positives may be preferable for cardiac safety profiling of limited sets of compounds.
|Plate cells
|6,500 CHO-hERG cells
|BD Biocoat poly-d-lysine–coated 384-well plate, clear bottom for imaging
|Incubation time
|Cell growth
|37°C and 5% CO2
|FluxOR loading
|25μL/well, 90min
|Dye loading
|1:1,000 FluxOR at ambient temperature in the dark
|Assay buffer
|Extra dye removal and buffer replacement
|1×HBSS buffer
|Compounds and controls
|1 or 10μM
|Stock concentration is 7.5 or 75μM; positive control (1μM dofetilide) wells I1–P2 and A23–H24; negative control (assay buffer with 0.02% or 0.2% DMSO) wells I23–P24; blank controls (Tl+ free) wells A1–H2, library compounds wells A3–P22
|Compound incubation
|Compound equilibrium
|Ambient temperature in the dark
|Channel stimulation
|Channel activation
|Channels are activated by addition of 5× Cl−-free stimulus buffer containing 55.8mM K+ and 14mM Tl+
|Assay readout
|Fluorescence detection
|Hamamatsu FDSS 6000 kinetic imaging plate reader, excitation filter 480nm, emission filter 520nm, detect at 1Hz for 120s
CHO, Chinese hamster ovary; DMSO, dimethyl sulfoxide; HBBS, Hanks balanced salt solution; hERG, human Ether-à-go-go related gene; Tl+, thallium.
|Add external buffer
|Prime plate
|External buffer: 137mM NaCl, 4mM KCl, 1mM MgCl2, 1.8mM CaCl2, 10mM HEPES, and 10mM glucose, pH 7.4
|Hole test
|0 to −10mV
|Test plate
|0mV step to −10mV
|Plate cells
|6,000 CHO-hERG cells
|Population patch-clamp mode plate, each well with 64 holes
|Seal test
|−70 to −80mV
|Cell seal test
|−70mV step to −80mV for 160ms
|Incubation with amphotericin B
|Membrane perforation
|Amphotericin B in internal buffer (40mM KCl, 100mM K-gluconate, 1mM MgCl2, 5mM HEPES, pH 7.2) and perforate for 70s
|Detect currents
|Trace recording
|Cells held at −70mV, stepped down to −80mV for 100ms, depolarized to −30mV for 100ms and to +20mV for 2s, hyperpolarized to −30mV for 2s, held at −70mV for 3s, depolarized to +40mV for 2s, and hyperpolarized to −30mV for 2s
|Compounds and controls
|3.5μL/well, 3min
|Stock concentration is 3μM; positive control (1μM dofetilide) columns 2 and 23; negative control (external buffer with 0.02% DMSO) columns 1 and 24, library compounds columns 3–22
|Detect currents
|Trace recording
|Recording protocol is the same as step 6
The authors thank the members of both Li laboratory and JHICC for valuable discussions and comments on the manuscript. This work was supported by grants from the National Institutes of Health (GM078579, MH084691).
No competing financial interests exist.
PubMed Central Canada is a service of the Canadian Institutes of Health Research (CIHR) working in partnership with the National Research Council's national science library in cooperation with the National Center for Biotechnology Information at the U.S. National Library of Medicine(NCBI/NLM). It includes content provided to the PubMed Central International archive by participating publishers.


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Pantaloons and Power: Nineteenth-Century Dress Reform in the United Statesby Gayle V. Fischer
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Pub. Date: 03/05/2001
Publisher: Kent State University Press
In Pantaloons and Power Gayle V. Fischer/i>
By the early nineteenth century clear definitions had developed regarding how American women and men were supposed to appear in public and how they were meant to lead their lives. As men's style of dress moved from the ornate to the moderate, women's fashions continued to be decorative and physically restrictive.
In Pantaloons and Power Gayle V. Fischer depicts how the reformers' denouncement of conventional dress highlighted the role of clothing in the struggle of power relations between the sexes. Wearing pantaloons was considered a subversive act and was often met with social ostracism.
This carefully researched interdisciplinary study successfully combines the fields of costume history, women's history, material culture, and social history to tell the story of one highly charged dress reform and its resonance in nineteenth-century society.
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Skip to comments.CIA gives grim warning on European prospects
Posted on 01/16/2005 8:38:31 AM PST by Pikamax
CIA gives grim warning on European prospects
THE CIA has predicted that the European Union will break-up within 15 years unless it radically reforms its ailing welfare systems.
The report by the intelligence agency, which forecasts how the world will look in 2020, warns that Europe could be dragged into economic decline by its ageing population. It also predicts the end of Nato and post-1945 military alliances.
In a devastating indictment of EU economic prospects, the report warns: "The current EU welfare state is unsustainable and the lack of any economic revitalisation could lead to the splintering or, at worst, disintegration of the EU, undermining its ambitions to play a heavyweight international role."
It adds that the EUs economic growth rate is dragged down by Germany and its restrictive labour laws. Reforms there - and in France and Italy to lesser extents - remain key to whether the EU as a whole can break out of its "slow-growth pattern".
Reflecting growing fears in the US that the pain of any proper reform would be too much to bear, the report adds that the experts it consulted "are dubious that the present political leadership is prepared to make even this partial break, believing a looming budgetary crisis in the next five years would be the more likely trigger for reform".
The EU is also set for a looming demographic crisis because of a drop in birth rates and increased longevity, with devastating economic consequences.
The report says: "Either European countries adapt their workforces, reform their social welfare, education and tax systems, and accommodate growing immigrant populations [chiefly from Muslim countries] or they face a period of protracted economic stasis."
As a result of the increased immigration needed, the report predicts that Europes Muslim population is set to increase from around 13% today to between 22% and 37% of the population by 2025, potentially triggering tensions.
The report predicts that Americas relationships with Europe will be "dramatically altered" over the next 15 years, in a move away from post-Second World War institutions. Nato could disappear and be replaced by increased EU action.
"The EU, rather than Nato, will increasingly become the primary institution for Europe, and the role Europeans shape for themselves on the world stage is most likely to be projected through it," the report adds. "Whether the EU will develop an army is an open question."
Defence spending by individual European countries, including the UK, France, and Germany, is likely to fall further behind China and other countries over the next 15 years. Collectively these countries will outspend all others except the US and possibly China.
The expected next technological revolution will involve the convergence of nano, bio, information and materials technology and will further bolster China and Indias prospects, the study predicts. Both countries are investing in basic research in these fields and are well placed to be leaders. But whereas the US will retain its overall lead, the report warns "Europe risks slipping behind Asia in some of these technologies".
For Europe, an increasing preference for natural gas may reinforce regional relationships, such as those with Russia or North Africa, given the inter-dependence of pipeline delivery, the report argues. But this means the EU will have to deal with Russia, which the report also warns "faces a severe demographic crisis resulting from low birth rates, poor medical care and a potentially explosive Aids situation".
Russia also borders an "unstable region" in the Caucasus and Central Asia, "the effects of which - Muslim extremism, terrorism and endemic conflict - are likely to continue spilling over into Russia".
The report also largely en dorses forecasts that by 2020 Chinas gross domestic product will exceed that of individual western economic powers except for the US. Indias GDP will have overtaken or be overtaking European economies.
Because of the sheer size of Chinas and Indias populations their standard of living need not approach European and western levels to become important economic powers.
The economies of other developing countries, such as Brazil, could surpass all but the largest European countries by 2020.
We're not that far behind the Euro-peons.
That's weird. A CIA assessment I agree with.
It also predicts the end of Nato..
NATO is already just about dead. NATO's almost token help in Afghanistan and nonexistent help in Iraq have taken care of that. We may be pulling out of Bosnia and Kosovo in the next couple of years. After that, it's all over except for the funeral.
Nothing here freepers haven't been saying for a LONG time.
There was an earlier thread comparing the economies of EU countries to US state economies. The best countries of the EU would only beat out 4 or 5 US states if compared individually. (been searching, can't find the right key words yet, will post link if I can find it).
Our "peons" have a standard of living better than the middle or even upper middle class in European countries, when measured in terms of income, food, housing, possessions such as cars, TVs, microwaves, etc.
Next big CIA discovery.............STEAM!!
It's actually fascinating reading.
Maybe once they drop the Euro I can afford to go back. ;)
If the CIA says 15 years, it's probably more like three.
Now when would the CIA find time to do something that might enhance our national security? They've got much more important things to do, like trying to oust Porter Goss so they can go back to undermining President Bush full time, instead of only part time like they're forced to do now.
How europe deals with immigration is going to have a lot to do with how their economies perform, and what their national identities look like in the future.
If European nations were admitted as states into the America union, they would be our poor, dependent cousins.
If the UK, France, or Italy became U.S. states, they would rank as the 5th poorest of the states, ahead only of Arkansas, Montana, West Virginia, and Mississippi. The richest EU country - Ireland - would be the 13th poorest. Sweden would be the 6th poorest.
Good economic development, in other words, results in even poor people being relatively well off in the states, wrote Dr. Fredrik Bergström, President of The Swedish Research Institute of Trade, Robert Gidehag in the book Sweden versus the US.
Hence, the EU no longer is or is seen as the great economic liberator of Europe.
In other words, a redneck driving a pick-up with a gun rack lives better than European gentry.
In the 1990s, U.S. growth was twice that of Europes, and three times that of Japans. The U.S. per capita income is now 55% higher than the EU-15 average, and 50% higher than Japans.
Thank you. That's the info.
Was it in the full text of this CIA report? Where did you find it?
The EU shouldn't be too worried, the CIA doesn't have a good track record.
15 years? I say about 3. Not from welfare but from bitterness over a bunch of Franco Dictator types.
Dog Gone,
The point I am making is that maybe less than 2 births per Russian woman is a good thing right now. Apparently, the people doing the birthing agree that it is. The individuals might have a good idea of what is best for them and their offspring, maybe even better than some liberal "reporters" or professional state planners/demographers.
If we just respond to this so-called "problem/crisis" in a positive way or view instead of thinking that the easiest/best remedy is simply replacing a declining population with a sea of new immigrants, be they Christian, Moslem or any other group. Infinite population growth may not be the best answer to economic or standard of living issues. There may be a better way. In fact, the population of these places may be seeking its own sustainable level given our technology and culture. Let's not be too fast to apply a political solution to an economic "problem" that may be solving itself.
Just an unusual thought, I guess.
Big demand for Finish to Maltese translators and interpreters.
Unusual, yes
The European declining population problem began in the 60's. In the 70's for instance, Germany started paying people a monthly amount for each child in order to encourage growth.
It didn't work
La Dolce Vita took over and the populous became too lazy to breed.
Now they have a huge financial problem. An aging population, promises of high retirement and worryfree living. Someone has to pay for it. When a Government already taxes you to the hilt, there isn't much left.
In short, "old Europe" has a problem that should have been adressed decades ago. They decided to bury their heads in the sand and left their collective A***es up high for target practise.
Perhaps the solution is to greatly reduce the social spending, but that certainly has political and social ramifications. Regardless, these countries will be forced into some tough choices.
We both know that "old" and "new" refer to the EU, not as a contrast to the US.
Like selling weapons to China.
"Old Europe" means the original 13
"New Europe" means new members.
This is not meant as a put down of any kind. Don't try to read things that aren't there.
Muslims will break up Europe quicker than 15 years.
Yes, but what is their democratic age? Many, if not all I would venture a guess, are younger Democratic countries then we.
The biggest problem in Germany was the "Wirtschaftswunder".
The only thing missing was that it didn't come with instructions.
Even if the birth rate would go to 3, it could not prevent the upcoming fiscal problem.
Old Europe is pouring in a lot of money into the new countries. They will want it back in the future to pay for their self made social system which is already bankrupt.
That's when the real problems begin.
"Old Europe needs new Europe more than the other way around.
read later
Interestingly, though, it too will have a demographic bubble to deal with, thanks to its one-child policy.
That will be the end of them. No modern free society can survive that. If this forecast proves true, and there are that many Muslims(a good portion WILL be radical), there will be mass murder and chaos. Their PC view of the world will leave them paralyzed and they will doing nothing to resist it.
Anticipating what the world will look like next year, in ten years, in 20 years, even 50 years is a fundamantal part of our ability to survive that world. How different would the world have been if we had properly predicted the current role of Islamic fundamentalism during Jimmy Carter's days, and had reacted to the revolution in Iran accordingly?
The CIA should be working many priorities, but I agree that anticipating the political situations in Europe, Africa, and South America are certainly among them.
Disagree. But do try to back up your claim that Jews are the cause of most of the world's problems.
Well, I did a typo.
I should have said "Old Europe" would include the original 6
I guess it always depends on the timing in a fast changing world?
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>>"L" glass is another class of pro lenses. Usually,>from what I see of the ads, specialized. Something about the>chemistry of the glass helps the predictability of the>refraction, aids in clarity, and cuts down on chromatic>aberration. Like aviation gasoline doesn't make a motor more>powerful, but it allows engineers to tweak the motor to get a>better power to weight out of it. >John, The "L" lenses you see are only a designation used by Canon. It is a designation they use as part of the lens description for their best lenses. They are not specialized lenses. It is the same as Nikon using the gold ring for their best lenses. Canon also adds a red ring on their L lenses. Len
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