WO1989007255A1 - Procede et dispositif de detection de reactions d'hemagglutination - Google Patents

Procede et dispositif de detection de reactions d'hemagglutination Download PDF

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Publication number
WO1989007255A1
WO1989007255A1 PCT/US1989/000296 US8900296W WO8907255A1 WO 1989007255 A1 WO1989007255 A1 WO 1989007255A1 US 8900296 W US8900296 W US 8900296W WO 8907255 A1 WO8907255 A1 WO 8907255A1
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WIPO (PCT)
Prior art keywords
well
blood
donor
image
positive
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PCT/US1989/000296
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English (en)
Inventor
Louis M. Mezei
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Cetus Corporation
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Publication of WO1989007255A1 publication Critical patent/WO1989007255A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/75—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
    • G01N21/77—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
    • G01N21/82—Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a precipitate or turbidity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/80—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving blood groups or blood types or red blood cells

Definitions

  • the invention pertains to the field of processing the results of chemical assays.
  • the invention pertains to the field of analysis of the light reflectance properties of patterns of hemagglutination reactions between donor cells and chemical reagents such as are used in antibody testing and blood grouping.
  • the invention also pertains to characterizing reactions between donor plasma and known reagent cells (backtyping in the blood typing art) or for characterizing reactions in antibody screen testing or infectious disease testing.
  • plate readers which are used to identify the pattern of positive and negative reactions between donor cells and certain chemical reagents used for antibody testing and blood grouping.
  • donor red blood cells and donor plasma are placed in two groups of transparent assay wells. Then a series of different reagents are added to the wells. If a positive reaction occurs in any well, hemagglutination results. Hemagglutination is the process of binding of the chemical reagent to donor cells to form clumps of cells which fall to a tight pellet at the bottom of the assay well when they are spun in a centrifuge. Thus, a positive reaction will be characterized by the presence of these clumps of cells in the bottom of the assay well.
  • a negative reaction will not result in large clumps of cells being formed which fall to the bottom of the test well.
  • the pattern of positive and negative reactions to the various reagents determines what ABO group and type of blood the donor cells came from. Similar techniques apply in the field of antibody screening tests.
  • the positions that the plate reader is set to can be simply stated as "off center”. If a negative reaction has occurred, the light absorbance reading will indicate much less light has reached the sensor along the path through the location outside the button. If a positive reaction has occurred such that a "button" has formed, the light absorbance readings along the path will be very low.
  • the light in the light beam which is not passed through the well bottom center is scattered by the terrace steps.
  • a conventional plate reader attempting to read such a well in a conventional manner might misinterpret the light absorbance pattern of a positive reaction for the light absorbance pattern of a negative reaction by getting low light absorbance readings on both paths.
  • the use of precisely located light beam paths in conventional plate reader technology places a requirement that the plate position in the plate reader be very precisely controlled so that the path that the light beam takes through the bottom of the well is predictable.
  • the apparatus is comprised of an IBM AT CPU driving a flat bed scanner.
  • the flat bed scanner scans and digitizes the light absorbance characteristics of the bottoms of the wells and sends this data to the CPU for processing.
  • the CPU then processes the data by reading a. configuration file to determine what type of wells are in use.
  • the data is retrieved for the first well bottom image and reconstructed to its uncompressed format.
  • a branch is then made to either of two pattern recognition subroutines depending upon the condition of a variable set from the data from the configuration file or user input defining the type of well bottoms in use.
  • the CPU averages the light intensity values of the pixels in the center region where the flat spot occurs and compares this average to the average light intensity for the pixels outside the center flat region of the well bottom. If the averages are substantially different, the well identification number is stored along with data indicating the reaction in the well was negative. If the averages are not substantially different, the well identification is stored along with data indicating that the well reaction was positive. Processing then returns to a point in the program where the pixel data for the next well to be analyzed is retrieved. The above noted pattern recognition process then repeats itself.
  • the pixel data for the well bottom center is averaged and compared to the average for the region outside the center of the well. If the averages are substantially different, the well identification is stored with data indicating that the reaction is positive. If the averages are not substantially different, the well identification. is stored with data indicating that the well reaction is negative.
  • Processing then returns to a place in the program to retrieve the pixel data for the next well to be examined.
  • a branch to the proper well bottom shape pattern recognition routine is made. For terraced bottoms, each pixel is compared to its neighbors.
  • the well reaction is determined to be negative. Otherwise, it is determined to be positive since no sharp contrast edge appears in the optical absorbance data appears. If a U-shaped bottom is in use, the same comparison process is used, but a large difference in one or more of the comparisons indicates that a positive reaction has occurred whereas the absence of a large difference indicates that a negative reaction has occurred.
  • the well data for each donor sample i.e., the reaction template for that donor
  • the well data for each donor sample is compared to known templates for the various blood types or assay results which are possible. If there is a match with any known template, that donor identification record in a data base is updated with the blood type and group or with the results of the particular assay which was performed.
  • the above defined apparatus and method may be generalized for any use which creates a pattern of light and dark areas of light absorbance in a pattern which convey information.
  • the computer may determine the pattern of light and dark area and compare this pattern to a group of known patterns. Such a machine can find use in may different antibody assays and in infectious disease testing.
  • Figure 1 is a block diagram of the hardware of the computer system which implements the invention.
  • Figure 2 is a digitized image of a plurality of terraced well bottoms some of which have experienced positive agglutination reactions, some of which have experienced negative agglutination reactions and some of which are empty.
  • Figure 3A is a diagram of a terraced well bottom showing what happens to the agglutination particles during a positive reaction as they are centrifuged out of solution.
  • Figure 3B is a diagram of a U-shaped well bottom showing what happens to the agglutination particles during a positive reaction as they settle out of solution.
  • Figures 4A and 4B are a flow diagram illustrating a typical pattern recognition process which could be used to implement the teachings of the invention in the field of blood typing and grouping.
  • Figure 5 is a flow diagram of the process of matching the pattern of positive and negative agglutination reactions to a plurality of known patterns of positive and negative agglutination reactions to the same reagents for known blood types.
  • FIG. 1 there is shown a block diagram of a computer system which implements the preferred embodiment of the invention.
  • the invention can be implemented in any computer 10 that is capable of driving a flat bed scanner 12 and which has the memory capacity to store the digitized data generated by the flat bed scanner 12.
  • the computer 10 is capable of driving a flat bed scanner 12 and which has the memory capacity to store the digitized data generated by the flat bed scanner 12.
  • the computer 10 is capable of driving a flat bed scanner 12 and which has the memory capacity to store the digitized data generated by the flat bed scanner 12.
  • the computer 10 that is capable of driving a flat bed scanner 12 and which has the memory capacity to store the digitized data generated by the flat bed scanner 12.
  • the computer 10 that is capable of driving a flat bed scanner 12 and which has the memory capacity to store the digitized data generated by the flat bed scanner 12.
  • the computer 10 that is capable of driving a flat bed scanner 12 and which has the memory capacity to store the digitized data generated by the flat bed scanner 12.
  • the computer 10 that is capable of
  • the computer 10 It is only necessary that the computer 10 have sufficient hard disk storage to store enough pixel data from the flat bed scanner 12 to define one plates worth of well bottom's light reflectance data. Generally, this is about 1 megabyte of pixel data. Further, the computer 10 must have sufficient RAM to run the driver software for the flat bed scanner 12, the operating system, and the pattern recognition program to be described below. Generally, an IBM AT with 640K of RAM and a 20 megabyte hard disk will be adequate for purposes of practicing the invention.
  • the flat bed scanner is a Data Copy Scanner which is commercially available. This scanner comes with a driver board which is coupled to the data, address and control buses of the computer 10 via an expansion slot. There is also driver software which comes with the flat bed scanner called PC
  • the flat bed scanner works in a manner which is well known to those skilled in the art and is similar to making a photocopy.
  • the scanner includes a light bar (not shown) which moves along under a glass plate 14 similar to that found on well known copy machines.
  • the light from the light bar is projected against the bottom of a plate 16 of test wells including wells 18 and 20.
  • the image of the bottom of the wells of plate 16 contains light and dark area depending upon the optical properties of the wells and upon the type of reactions that have occurred in each well.
  • the image of the bottoms of the wells is digitized by the flat bed scanner 12, and the data is output to the CPU 10 on the bus 22.
  • the CPU 22 stores this digitized image of the well bottoms on a hard disk (not shown).
  • the CPU 10 is controlled through a keyboard 24 and displays messages to the operator by a monitor 26.
  • a monitor 26 Referring to Figure 2, there is shown a representation of the actual light and dark patterns in a digitized image of the bottoms of a plurality of test wells. Some of these test wells have donor samples which have experienced positive reactions, and some of the test wells have donor samples which have experienced negative reactions. Some of the test wells are empty.
  • the wells labeled with reference numbers 28, 30 and 32 contain donor material which has experienced negative reactions with reagent material added to the wells, i.e., no agglutination has occurred.
  • a key feature of the method and apparatus of the invention is to be able to distinguish between these various empty, positive and negative wells by the shapes and locations of the light and dark spots in the digitized image of the bottom of each assay plate.
  • any pattern recognition software which can make such distinctions and identify the wells as they have been identified in Figure 2 will suffice for purposes of practicing the invention.
  • Figure 3A shows a terraced bottom shape such as is found in the Olympus microtitre plate.
  • the particles such as the particle 40 which are shown as falling out of solution represent agglutinations between donor cells and the reagent chemical or cells added to the well. These particles are shown as falling out of solution toward the bottom of the well. If a negative reaction had occurred, no such particles would exist, and the solution of donor cells or plasma plus reagent would have equal light absorbance throughout its volume. Note because of the terrace steps having flat tops which are normal to the gravity vector, the agglutination particles come to rest on the bottom and stay where they fall since there is no slope toward the center on the top of any particular step.
  • the entire bottom of the well becomes coated with particles thereby creating a uniform film of light absorbing material. If light is directed toward the entire bottom surface 42 and the image of the bottom surface 42 is digitized, the image will have a uniform light absorbance property throughout its area. Note that one of the reasons why reading light absorbance of individual conventional light beams as is done in plate readers is not accurate is apparent from study of Figure 3A.
  • a light beam 44 would be directed through the substantially flat center section 46 of the plate for a first reading. The light beam would pass through the center section on a straight path unless it was blocked by a film of agglutination particles resulting from a positive reaction. The amount of light intensity in the light beam after it passed through the bottom would then be measured.
  • the light beam would then be deflected to pass through the bottom on a second path shown at 48.
  • This path is set to not pass through the center of the well bottom.
  • this light beam gets scattered as symbolized by the beam components 50 and 52 as it passes through the bottom of the well because of the sharp edges in the material of the well bottom caused by the terraces.
  • Figure 3A is not drawn to scale, and, in reality, there are hundreds or thousands of terrace steps in the bottom of each well. This scattering would be interpreted falsely as light absorbance even though there may be no particles resting on the bottom of the well from a positive reaction.
  • the light scattering in the region outside the area of the center flat section of Figure 3A defined .by the diameter D creates the distinctive patterns of light and dark regions shown in Figure 2 for wells 28, 30 and 32.
  • the dark center regions in these wells indicate flat center regions 46 where no positive reaction agglutination particles are reflecting or absorbing light.
  • the light shined up from the bottom passes straight through the flat center section 46 and is not reflected back to the surface where the image to be digitized is focused thereby creating a dark spot in the image.
  • some of the scattered light is scattered back toward the surface on which the image to be digitized is focused thereby creating a relatively lighter area in the image. This contrast can be detected as a negative reaction.
  • a positive reaction will result in an image of the bottom which has a relatively uniform light intensity throughout the perimeter of the well bottom.
  • FIG. 3B there is shown an illustration of a U-shaped bottom. Again, agglutination particles such as the particle 54 are shown falling to the bottom of the well. This occurs under the influence of centrifugal force in a centrifuge. A difference between the U-shaped bottom and the terraced bottom is that when the agglutination particles reach the bottom of the well, they slide along the bottom until they reach the center during the spinning on the centrifuge. The particles 56 and 58 are shown sliding toward the center bottom of the well under the influence of centrifugal force. At the center bottom of the well, a "button" 62 of agglutinated material exists.
  • This button 62 block or absorbs light in a beam 64 directed through the center bottom of the well in a conventional plate reader and forms dark spot in the center of a digitized image of the bottom of a well formed by a flat bed scanner.
  • a second light beam path shown at 66 directed off center through an area not occupied by the center button in a conventional plate reader passes through the well bottom and is bent but no substantial scattering occurs and no substantial light absorption occurs because the light beam does not pass through the button 62. If no positive reaction occurred, the button 62 would not be formed, and both light beams 64 and 66 would experience approximately the same light absorption.
  • a plate reader of conventional design can distinguish between positive and negative reactions by comparing the light intensity values of the two beams 64 and 66.
  • the digitized image of the bottom of a U-shaped well which has had a negative reaction will be substantially uniform in light intensity throughout the area of the bottom.
  • suitable pattern recognition software can distinguish between positive and negative reactions by looking for a contrasting light intensity between the center area of the well and the surrounding areas.
  • Step 68 represents the process of either reading a configuration file or prompting for and receiving user input, from the keyboard as to whether U-shaped bottoms or terraced bottoms are in use.
  • step 70 the digitized image data for the next well bottom to be analyzed is retrieved from disk. In some embodiments multiple well bottom images may be simultaneously accessed and analyzed. In the preferred embodiment, only one well bottom is analyzed at a time.
  • Step 72 represents a test to determine whether the last well in a plate has been processed. If so, processing is vectored to a well pattern template matching routine which will be discussed later.
  • the purpose of this template matching routine is to compare the pattern of positive and negative reactions to known patterns or
  • step 74 decodes the compressed data to reconstruct the pixel data representing the actual image as digitized.
  • the next step is to start the pattern recognition process of comparing light intensity values in various areas of the picture. This is symbolized by step 76.
  • This step is the process of averaging the light intensity values of pixels in the center region of the image and comparing the average to the average light intensity of the pixels in the regions surrounding the center region. How to define the size and shape of the center region may be defined in the configuration file or, in some embodiments, may be defined interactively by the user in real time on a reproduction of the well bottom image displayed on the monitor.
  • step 76 processing branches to the proper subroutine to use the results of step 76 to decide whether the reaction was positive or negative. Since the conclusions are opposite depending upon which well bottom shape is in use, before the branching can occur, the decision as to which well bottom shape led to the image being processed must be made. This decision is made in step 78.
  • This branching step looks at the data read from the configuration file to determine which well bottom shape created the image being processed and causes branching to step 80 if a terraced bottom was used and to step 82 if a U-shaped bottom shape was used.
  • Step 80 is a test to examine the results of the calculations performed in step 76 and to branch to the proper routine to label the well ID number with the reaction type depending upon the result. For terraced shaped bottoms, if there is a substantial difference between the average center section light intensity and the outer region light intensity, then the reaction is negative in the terraced bottom wells . The reaction is positive is there is no substantial difference between these light intensity averages. Step 80 takes the two region averages and compares them for a substantial difference. Typically, this would be done by subtracting the two values and comparing the difference to a threshold constant which could be stored in the configuration file or, in some embodiments, could be supplied interactively by the user.
  • step 80 processing is vectored to step 83 where the well identification record in a data base having records for each well is updated.
  • Each well record contains a field for the reaction type. This field is updated with data indicating the reaction type is negative if step 83 is reached. If no substantial difference is found in step
  • processing is vectored to step 84 where the well data base record is labeled with a positive reaction type data in the appropriate field. Processing then returns to step 84
  • step 78 If processing in step 78 resulted in a transfer to step 82, the conclusions drawn will be exactly opposite as were drawn in step 80 since U-shaped bottoms look different.
  • Step 82 again compares the center section average to the outer region average in the same way as was done in step 80. If a substantial difference is found between the center region average and the outside region average, then processing is vectored to step 86 where the well identification record in the data base is updated to indicate a positive reaction occurred. If no substantial difference is found, step 88 is. reached where the well record is updated to indicate a negative reaction occurred. Processing then returns to step 70 where the digitized data for the next well to be analyzed is retrieved from the hard disk.
  • Step 90 is the first step in the process of template matching and involves accessing the well data base and retrieving the well reaction types for all wells having the same donor identification.
  • Each well record in the data base has a field for the donor identification number of the donor whose red blood cells or plasma were deposited in the well.
  • Each well record has a field that identifies the type of donor sample (red blood cells or plasma) that went into the well and the type of reagent that went into the well. All this data for all well records corresponding to a particular donor is retrieved in step 90.
  • Step 92 represents the process of comparing the reaction pattern of all the wells containing sample from the same donor to the template of reactions to the same group of reagents for known blood types .
  • the types of reagents used in the forward and back typing processes of blood grouping and typing assays and the pattern of positive and negative reactions to these various reagents is well known.
  • step 92 represents the process of comparing the well reaction pattern for the particular donor to all the known blood type templates, i.e., known patterns of positive and negative reactions to the same reagents. After this comparison, a determination is made as to whether any match occurred. In other embodiments, after each comparison a determination is made as to whether there was a match. If there was, then no further comparisons are made.
  • the pattern recognition and. template matching processes disclosed herein for blood typing and grouping assays are not the only use for the invention and the invention is not to be understood as limited to these types of assays.
  • the invention includes methods and apparatus for performing other assays and work such as the sequencing of DNA where the assay or other operation results or can result in an image which has light areas and dark areas which contain the sought after information.
  • Suitable pattern recognition programs which extract the information from the patterns of light and dark areas are to be understood as included within the scope of the invention.
  • the invention has equal utility in reading the patterns of light and dark area on the images of gels used to determine the sequence of nucleic acids in
  • DNA or RNA DNA or RNA.
  • Other applications for the invention include any assay which creates an agglutination button such as antibody assays.
  • test 94 a determination is made which template, if any, matched the experimentally determined reaction pattern of the donor.
  • processing is transferred to step 96 where the blood type and group of the matching template is written to the blood type and group records of a data record in another data base of donor identification records.
  • processing proceeds to step 98 where the appropriate donor identification record in the donor data base is updated to indicate this donor is an NTD or no type determined.
  • step 96 or 98 After either step 96 or 98 is performed, a step
  • step 100 is performed to determine if all the donor samples for which test results have been determined have been processed against the known templates. If the answer is yes, processing stops. If the answer is no, processing is vectored back to step 90 to retrieve the reaction results for the next donor to be matched.

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Abstract

Procédé et dispositif de reconnaissance de formes servant à traiter l'image numérisée de fonds de puits ou d'autres substances présentant des images lumineuses et sombres contenant des informations recherchées au cours d'une analyse ou dans d'autres opérations telles que la mise en séquence de l'ADN. Les motifs lumineux et sombres sont comparés avec des motifs stéréotypiques lumineux et sombres résultant d'analyses connues ou d'autres opérations connues, afin de déterminer un type pour une image obtenue de manière expérimentale. Lors d'une analyse visant à déterminer le type et le groupe sanguin, le motif de réactions positives et négatives aux réactifs de détermination du type sanguin utilisés dans les procédures directe et inverse de détermination du type sanguin est comparé avec des motifs connus pour déterminer le type et le groupe sanguin du donneur.
PCT/US1989/000296 1988-02-03 1989-01-24 Procede et dispositif de detection de reactions d'hemagglutination WO1989007255A1 (fr)

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EP0433005A2 (fr) * 1989-12-11 1991-06-19 Olympus Optical Co., Ltd. Méthode pour le jugement automatisé d'une configuration de particules
WO1998032004A1 (fr) * 1997-01-15 1998-07-23 Axis Biochemicals Asa Systeme diagnostique
WO2000005571A1 (fr) * 1998-07-23 2000-02-03 Axis-Shield Asa Reactions d'agglutination
WO2001071261A1 (fr) * 2000-03-21 2001-09-27 Freshman Flimmer Ab Dispositif de vanne de regulation d'ecoulement d'air
US6661501B1 (en) 1999-10-29 2003-12-09 Cytyc Corporation Cytological stain composition including verification characteristic
US6665060B1 (en) 1999-10-29 2003-12-16 Cytyc Corporation Cytological imaging system and method
US7006674B1 (en) 1999-10-29 2006-02-28 Cytyc Corporation Apparatus and methods for verifying the location of areas of interest within a sample in an imaging system
WO2008086632A1 (fr) * 2007-01-19 2008-07-24 Tudor Arvinte Procédé et appareil permettant de détecter e t d'enregistrer les propriétés d'échantillons
US20140112558A1 (en) * 2012-10-22 2014-04-24 Qiagen Gaithersburg, Inc. Automated pelletized sample vision inspection apparatus and methods
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CN109932517A (zh) * 2019-04-04 2019-06-25 烟台海深威医学技术有限公司 一种血液凝集判断方法及装置

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Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0433005A3 (en) * 1989-12-11 1992-06-03 Olympus Optical Co., Ltd. Automatic particle pattern judging method
US5162234A (en) * 1989-12-11 1992-11-10 Olympus Optical Co., Ltd. Automatic blood cell particle pattern judging method
EP0433005A2 (fr) * 1989-12-11 1991-06-19 Olympus Optical Co., Ltd. Méthode pour le jugement automatisé d'une configuration de particules
WO1998032004A1 (fr) * 1997-01-15 1998-07-23 Axis Biochemicals Asa Systeme diagnostique
AU733351B2 (en) * 1997-01-15 2001-05-10 Axis-Shield Asa Diagnostic system
AU758339B2 (en) * 1998-07-23 2003-03-20 Axis-Shield Asa Agglutination assays
WO2000005571A1 (fr) * 1998-07-23 2000-02-03 Axis-Shield Asa Reactions d'agglutination
US7006674B1 (en) 1999-10-29 2006-02-28 Cytyc Corporation Apparatus and methods for verifying the location of areas of interest within a sample in an imaging system
US6661501B1 (en) 1999-10-29 2003-12-09 Cytyc Corporation Cytological stain composition including verification characteristic
US6665060B1 (en) 1999-10-29 2003-12-16 Cytyc Corporation Cytological imaging system and method
US7411664B2 (en) 1999-10-29 2008-08-12 Cytyc Corporation Cytological imaging system and method
US7538861B2 (en) 1999-10-29 2009-05-26 Cytyc Corporation Cytological imaging system and method
WO2001071261A1 (fr) * 2000-03-21 2001-09-27 Freshman Flimmer Ab Dispositif de vanne de regulation d'ecoulement d'air
WO2008086632A1 (fr) * 2007-01-19 2008-07-24 Tudor Arvinte Procédé et appareil permettant de détecter e t d'enregistrer les propriétés d'échantillons
US9417176B2 (en) 2007-01-19 2016-08-16 Tudor Arvinte Method and apparatus for detecting and registering properties of samples
US20140112558A1 (en) * 2012-10-22 2014-04-24 Qiagen Gaithersburg, Inc. Automated pelletized sample vision inspection apparatus and methods
WO2014066226A1 (fr) * 2012-10-22 2014-05-01 Qiagen Gaithersburg, Inc. Appareil d'inspection de vision d'échantillons en pastilles automatisé
US9135515B2 (en) 2012-10-22 2015-09-15 Qiagen Gaithersburg, Inc. Automated pelletized sample vision inspection apparatus and methods
US9212976B2 (en) 2013-03-15 2015-12-15 Qiagen Gaithersburg, Inc. Vision-guided aspiration apparatus and methods
CN109932517A (zh) * 2019-04-04 2019-06-25 烟台海深威医学技术有限公司 一种血液凝集判断方法及装置

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IE890284L (en) 1989-08-03
AU3057689A (en) 1989-08-25

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