Background technology
The at present acceptable method of the microscopic particles that causes a disease of distinguishing needs the process long duration, labour-intensive.For example, in potable water, whether exist Pa Womushi to conceal spore (Cryptosporidium parvum) or Lan Baishi flagellate (Giardia lamblia), the supplier must adopt a kind of long, labour-intensive program-USEPA method 1622 in order to judge.Clinical laboratory and Food Inspector also must adopt long, labour-intensive program to search and distinguish harmful bacteria.
Unfortunately, can not wait for definite judgement in many cases to microorganism.Must before supplying water, just identify of the pollution of latent spore immediately to potable water to family.Equally, the cause of disease of distinguishing meningitis and so on disease also usually can not be waited for the time that needs.At last, detect in most cases and distinguish that the bacterium in the food source of beef and so on has expended the too many time, to such an extent as to before pinpointing the problems, just the food branch has been sent out.
The method and apparatus that various detection microcosmic biosomes have been arranged.For example, people such as De Leon are in U.S. Patent No. 5,770, have provided a kind of method that detects latent spore in 368.Adopt specified genus or the specific kind of peculiar primer of protozoan (primer) to synthesize cDNA, then cDNA is carried out the enzyme amplification, can judge the viability or the infectivity of cystozooid from inducing HSP RNA template.For or, can be by adopting specified genus or planting the peculiar primer of protozoan and judge infectivity from the HSP DNA of infected cell to (primer pair) amplification.
People such as Steele are in U.S. Patent No. 5,693, disclose the method that detects the latent spore of Pa Womushi in 472.The Method and kit for bag that detects the latent spore of Pa Womushi in the water sample of superficial water or ight soil and so on or biological sample has been described.This method depends on all or part of feature that adopts primer to detect at least one dna sequence dna of the latent spore of Pa Womushi, and this sequence is to be included in all or part of chromosomal region among plasmid recombinant pINV38G and the pHem4, that be called 38G and HemA respectively.
People such as Pleass are in U.S. Patent No. 5,229, disclose the laser-Doppler spectrometer that the behavior of microcosmic biosome is carried out statistical research in 849.A kind ofly monitor and distinguish the modification method and the system of micropopulation of in liquid, moving about or in liquid, passing the surface, provide the small activity change of quick measurement, substantially at the sensitive method that detects and distinguish the single microbial in big volume liquid under the situation that has chip to exist.This system comprises laser station, sample collection station, camera station and monitoring station.
People such as Wyatt are in U.S. Patent No. 4,548, have provided the method and apparatus of distinguishing or characterize molecule in 500.Described based on measure equipment and the method that some the may observe optical quantities that produces characterized and/or distinguished single particulate when each particle passes a branch of light or other electromagnetic radiation.A branch of thin light, preferably, a branch of monochromatic linear polarized light sends incident light to one group of detector device by spherical detector array or fiber plant, and grain flow intersects at the center and the light beam of ball array.Selected observable quantity is calculated from detected scattered radiation, is used for then accessing specific mapping graph from computer memory arrangement, and each observed quantity all has a figure.
People such as Lee are in U.S. Patent No. 5,473, disclose a kind of interferometry temperature-sensing system with coupled laser diode in 428, wherein amplitude are adjusted to suitable with before feedback laser bundle.The interferometry temperature-sensing system provides the self-coupling effect that adopts the laser detection element accurately to handle the simplified design of interference pattern, and wherein, laser diode and optical detection elements are packaged together.
The U.S. Patent No. 5,582,985 of Curtis Thompson discloses the detection of mycobacterium.This invention provides method, complex and the kit of the mycobacterium in the test sample.This method is included in the nucleic acid probe of mycobacterium special use (nucleic acid probe) and sample mix (hybridizing) before, and sample is contacted with formalin, a kind of organic solvent and protein degradation.This invention is being particularly useful aspect detection and susceptibility screening (susceptibility screening) the human disease's property mycobacterium (as Much's bacillus).
Summary of the invention
Unique system of the present invention is measured for the various microscopic particles of distinguishing the protozoan that is suspended in liquid or the gas and other microorganism and so on provide accurately and effectively.Methodology of the present invention provides a kind of program that is used for qualitative and quantitative distinguishing particles kind, and this program source is in convenient and reliable mode, by the measurement of the light of one group of particle scattering of collecting around the optical sensor of suspended particle.
In more detail, the scattered light of suspended particle is detected and is converted into the electric signal of voltage and so on by sensor array.Voltage from each sensor enters correcting device assembly (modifyingmeans componet), and voltage is digitized herein, and the numerical value that obtains is used as the fingerprint that particle is distinguished.Unique correction assembly comprises the predictor formula that one or more groups one or more dimensions probability experience histogram is derived, the function of one or more mathematical combination that this histogram is a digitized voltage.Each group histogram is made up of single probability histogram, and these probability histograms provide the possibility of numerical value that is produced the particular combinations of viewed optional network specific digit voltage by a certain specific particle type.Like this, when predictor formula obtained the very big probable value of a certain particular types, the correction assembly of the uniqueness in the system of the present invention was understood as " particular types " with the signal that measures.
In one embodiment, fast detecting of the present invention and distinguish that microscopic particles comprises the steps: to carry out qualitative and method quantitative measurment
A) will treat in the control fluid that distinguishing particles is suspended in the sample chamber to be contained;
B) sample chamber is remained on the assigned direction with respect to an intense light source;
C) adopt described light source that the sample chamber is shone;
D) by collect and measure scattered light around one group of optical sensor of detection zone from the sample chamber;
E) when passing described intense light source, particle converts the output of the voltage of sensor array to digital signal; And
F) signal and the probability histogram storehouse that obtains compared, and the data that obtain are carried out the statistics classification, thereby the microscopic particles that exists is distinguished.
According to the present invention, this Nogata picture library is made up of the histogram that is included in a statistical classification algorithm of each particle type, the probability that the relevant signal of described algorithm computation is produced by those particle type.The special value scope associated frequency of the digitized voltage mathematical combination by measuring a kind of particulate and sensor obtains probability histogram empirically.Therefore, can that is to say for an One Dimension Analysis to generate the occurrence frequency histogram, perhaps, can a plurality of mathematical combination be that is to say a multidimensional analysis generated frequency histogram for a mathematical combination.
In preferred implementing form, equipment of the present invention comprises in the mode of combination:
A) the polarization laser of generation beam waist;
B) comprise the optical mount of a plurality of photo-detectors, each photo-detector along around place, and have no concealed ground towards laser light common convergence zone (common region ofregard) with a tight waist;
C) fill the sample chamber of fluid sample to be analyzed;
D) sample chamber is remained on respect on the with a tight waist assigned direction of laser light and remain on device in the common convergence zone of photo-detector;
E) make grain flow in the sample cross the device of laser beam waist;
F) cover light source and optical mount to produce the device of dark outer cover;
G) will convert the device of digital value by the measured light intensity value of detector to;
H) with the device of digital value continuously;
I) based on digitized measurement, judge at particle when enter device in the light beam at place, common convergence zone;
J) digitizing numerical value is converted to the device of calibration value;
K) extract the device of event descriptor from the event data of digitizing and calibration;
L) device of calculating discriminant score from event descriptor;
M) device of definition probability histogram, this histogram make can calculate the discriminant score that calculates from measured value be by specific particle type cause probability;
N) distinguish the device of effective discriminant function.
O) probability histogram and discriminant function are stored in the device of distinguishing in the storehouse, a probability histogram are arranged for each particle type that can be distinguished and each discriminant function;
P) recover the probability histogram of previous storage and the device of discriminant function, can adopt for each and distinguish that particle type and each discriminant function of distinguishing in the storehouse have a probability histogram;
Q) calculate the device of the probability of each particle type in the storehouse for set-point of discriminant function;
R) device that can adopt the probability of distinguishing each particle type of distinguishing in the storehouse to combine; And
S) distinguish the device of unknown particle based on threshold value.
Embodiment
The invention provides a kind of based on measurement data being carried out peculiar methods and equipment statistical study, that be used for the microscopic particles discriminating conduct.This method is based upon on three relevant parts (referring to Fig. 1): surveying instrument and original data processing system; The storehouse is distinguished in generation; And use and distinguish the storehouse.
The invention provides fast detecting and distinguish microorganism and the device of the particle of other type.This system measures and analyzes from the light of particle scattering during intense light source based on particle being passed collimation.When particle and incident light wavelength quite or when big slightly, scattering mainly takes place at the particle glazed thread, the energy distribution of scattered light is on all directions.Clearly the light intensity on all directions is decided by particle size and shape, and the incident light wavelength.Generally, can be from particle size and shape be calculated in the fine angular resolution measurement of light intensity and the electromagnetism phasometer of all scattered radiations.In fact, this is obtaining widespread usage when handling the radar signal of aircraft on Aero-Space.Yet when handling visible light is unpractical.In addition, the accurate size and the shape of the particle of measurement bacterium and so on are utterly useless for identification, because exist the difference of nature on size and dimension.According to the present invention, provide a kind of by only measuring the system that the sub-fraction scattered light comes distinguishing particles.By measurement result and the storehouse of before various particle being done to measure are compared, realize that particle is distinguished accurately.
With helping preferred embodiment is carried out more complete description to give a definition.
Term " fluid " express liquid or gas medium.
Term " light " expression electromagnetic radiation.
Term " common convergence zone " expression is by all visible little area of space of photo-detectors while.
Term " has no to cover " expression and does not have vision obstruction, distortion or vignette.
Term " transparent " is represented the wavelength of the light that is adopted transparent.
Term " sample chamber " expression fills the transparent housing of sample.
Term " detector " expression converts the electronic installation of voltage or electric current to light sensitive and with incident light, and the size of voltage or electric current is directly proportional with incident intensity.
Term " optical mount " representational framework, photo-detector and around the electronic equipment of sample chamber.
Term " is calibrated " expression raw measurement data is revised so that canonical measure causes correct value.
A kind of particle that term " particle type " expression is single is as a kind of microorganism or pollen or as types such as erythrocytes.
Measured one group of scattered light data when term " incident " is illustrated in particle and passes light beam.
Term " occurrence frequency histogram " expression is for the calculating of the given mathematical combination of particular measurement, and the measurement of particle type can cause the special value scope on many high-frequencies.
Term " probability histogram " expression normalization occurrence frequency histogram, thus the volume (multidimensional situation) under area under a curve (one dimension situation) or the curve is 1.
In a form of implementation, the method that is used for qualitative and quantitative measurment (third parts of three relevant portions), fast detecting and distinguishes microbe granular of the present invention adopts instrument as shown in Figure 2 and may further comprise the steps:
A) in the ultrahigh quality water of particle suspending that will be to be distinguished in being contained in vial;
B) sample bottle is fixed in the light laser light source, makes beam waist pass the center;
C) by collect and measure scattered light around the photosensor array of sample chamber from vial;
D) when passing intense light source, particle converts the output of the voltage of sensor array to digital signal; And
E) signal and at least one group of probability histogram that is obtained compared the microscopic particles that exists to distinguish.
Therefore, be by measuring earlier species numbers a large amount of on the statistical significance, from measure, deriving relevant information then and carry out to distinguishing of particle type.Collect and relevant information deposited in distinguish the storehouse after, be to be undertaken to distinguishing of unknown particle by new measurement and particle characteristic archive repository are compared.
The scattered light that this system has produced when having used particle to pass intense light source.The synoptic diagram that Fig. 2 represents to measure scattered light and sets up the storehouse and carry out a kind of form of implementation of the instrument that particle distinguishes.Optical mount provides the framework that supports photo-detector, and their ken is limited in single common convergence zone.The light intensity that scatters to outside the sample chamber is collected and measured to photo-detector.The voltage digitalization that the event handler subsystem produces detector continuously and monitor digitizing after voltage so that Dynamic Extraction background signal and judge when have particle to pass laser beam.
When event handler detected the particle that passes laser beam, processor kept the digitized voltage from each detector, passes completely through light beam up to particle.After particle passed light beam, event handler was calibrated, and extracts the required particular data (event descriptor) of particle discrimination algorithm then and descriptor is sent to the ID processor subsystem from digitalized data.
The ID processor subsystem uses event descriptor to form discriminant score, distinguishes that with particle type the storehouse contrasts.In the storehouse, comprise a lot of groups and can be used for calculating the probability histogram that viewed discriminant score results from the probability of specific particle type.ID processor probability of use histogram and statistical classification algorithm are derived the identity of the particle that passes light beam.The ID processor provides this particle identity on display.
Thereby the phase one of process of the present invention uses a large amount of measurements of being undertaken by surveying instrument to generate and distinguishes the storehouse.The subordinate phase of process of the present invention is used surveying instrument and is distinguished that the storehouse distinguishes unknown particle.
The understanding of the process that generates the storehouse is depended on understanding to the measurement data of spheric grain.When spheric grain passed collimated light beam, the photo-detector measurement was decided by the time correlation intensity that particle speed and laser cross-sectional strength distribute.Spheric grain also was Gaussian (annotate: particle is more much smaller than beam diameter) to the scattered light intensity of time when the cross-sectional strength that Fig. 3 is illustrated in laser was distributed as Gaussian.Therefore, (d, t) function as time t also is a Gaussian to the voltage v that measures on detector d.The same particle that passes beam waist along different paths can show the different Gaussian distribution of amplitude.Will be in each constantly measured value divided by eliminating this path dependence in the one or more detector value of synchronization sum.Thereby:
V ' (d, t)=v (d, t)/∑D 'V (d ', t) formula (1)
Here, d ' is some or all detectors.When particle was sphere, as long as signal intensity is enough big, (d t) was exactly constant to normalized value v '.The path independence of being walked when in addition, this numerical value also passes laser beam with particle.
The ratio of spheric grain is predictable in the formula (1) when wavelength, particle diameter, particle refractive index and fluid are known.Therefore for spheric grain, adopt single ratio just can characterize the particle that passes light beam from each detector.These single ratios from each detector are known as event descriptor, because they have described event source without peer, that is to say the particle of the incident of causing.Hereinafter, the event descriptor of ED (d) expression detector d that is to say ED (d)=v ' (d, t1), t wherein1It is particular moment.Each measure-alike spheric grain produces identical event descriptor ED (d).Therefore in principle, provide the measurement of spheric grain incident, just can derive particle diameter from the value of event descriptor.
When particle was not sphere, the event descriptor in the formula (1) no longer was a constant.(d, t) curve map to the time can not be a straight line to v '.The shape of curve is decided by the orientation of particle when particle passes the light velocity.When passing laser beam repeatedly, same particle will produce different curve shapes.Similarly, the variable grain of same particle type also can produce a series of curve shapes.As a result, above-mentioned event descriptor is decided by the time.Thereby, consider aspherical particle, the notion of event descriptor has broadened, and the data of the only characteristic event that refers to are not even descriptor numerical value is being constant aspect the time for particle type.
Discriminating conduct need be extracted the AD HOC of event descriptor from event data.Various patterns are arranged.Wherein two are:
The ED that 1. is chosen in the event procedure to be obtained (d, t)=(d, t) maximal value is as event descriptor numerical value for v '.That is to say EDd=max (v (d, t))/ΣD 'V (d ', t)).
2. specific detector d in event procedurenValue v ' (dn, when t) being maximal value, be chosen in time tnThe time value ED (d, tn)=(d tn) is event descriptor numerical value to v '.That is to say EDd=v (d, t 'n)/ΣD 'V (d ', t 'n)), t ' whereinnIt is the moment when detector d=n is maximum.
Because measured event data is decided by the orientation of particle when aspherical particle passes laser beam, given event descriptor numerical value, people are distinguishing particles directly.Yet it is that people can adopt the statistical analysis prediction for which kind of particle.Measure a plurality of same class particles and will produce a series of event descriptor numerical value.The numerical range that this series of values data of description descriptor is got.Should be noted that importantly numerical range is limited in certain limit.These measured values are depicted as occurrence frequency histogram to event description numerical value, can form the curve map that is similar to Fig. 4.Disclose as this curve map, the numerical range of event descriptor is restricted, and the more important thing is, other numerical value of some numeric ratios more likely.
Because particle size, shape or optical signature difference, the occurrence frequency histogram of variable grain kind will cause slightly different histogram curve.Fig. 4 represents the normalization histogram of three kinds of variable grain kinds: the polystyrene spheres sample that latent spore of Lan Baishi flagellate, Pa Womushi and diameter are 1.588 microns, event descriptor is ED1For given ED1Numerical value, as putting the α place in the drawings, it may be the latent spore of Lan Baishi flagellate or Pa Womushi that people can derive this particle.Similarly, if this numerical value is β, then this particle may be the spheroid of 1.88 microns of diameters.Yet distinguish not to be absolute.At a α and β, cause that by in three kinds of particles any chance of incident all also is not zero.
Obviously, the additional information of this process need is to improve the possibility of accurately distinguishing.Additional information is from different event descriptor ED2Deng another the group histogram.It is the probability that produced by variable grain from measured event descriptor numerical value in the histogram curve data set of measuring the in advance particle type of deriving that the process of distinguishing becomes.This normalization histogram data set of measuring in advance is known as distinguishes the storehouse.
Distinguish that the storehouse generation phase starts from from event data extracting event descriptor and handled by surveying instrument.Event descriptor is re-organized into one group of very big discriminant function.Calculate each function and the probability histogram that will be included in each the variable grain kind in the storehouse.Calculating provides the intensity of each discriminant function of distinguishing between kind and the kind.Discern best discriminant function and related data is stored, so that distinguisher uses.
Discriminant function has been strengthened the difference between the particle type.Consider the data of two different sphere diameters.People can find the ED of a spheroid1Value is greater than another spheroid, and the ED of first spheroid2Situation less than second spheroid.In this case, ratio ED1/ ED2It is good Discr. between two different spheroids.The ratio of a sphere diameter is greater than the ratio of another sphere diameter.In this case, by discriminant function DF=ED1/ ED2The histogram of the numerical value that produces shows two separation between the variable grain kind curve more significantly than the histogram of individual event descriptor.
Discriminant function is the popularization of event descriptor notion.For example, three relations between the following event descriptor are exactly each discriminant function: DF1=ED1, DF2=1/ED2, DF3=ED1/ ED2Because discriminant function comprises the individual event descriptor, discriminant function will be only adopted in discussion hereinafter.
Easier use histogram after the normalized.That is to say, be that 1 (one dimension situation) or the volume under curve are 1 (multidimensional situations) in area under a curve.The class of a curve that obtains is similar to probability density.These probability histograms can directly provide the probability that produces specific discriminant score from the measurement to specific particle type.
As indicated above, a probability histogram of each particle type can not classify as the incident that records specific particle type.Therefore need derive one group of density from one group of discriminant function.Unfortunately, as shown in Figure 4, the discriminant function that has may not can show the good separation of probability histogram curve to the variable grain kind.Between flagellate and spheroid and latent spore and spheroid, separate good in, between flagellate and the latent spore separate and bad.Therefore the discriminant function of being drawn among Fig. 4 does not provide identifying information difference useful between flagellate and the latent spore.Select which group discriminant function to be used to distinguish to be very crucial: the selection of discriminant function is not blindly.In addition, the reason of " priori " does not have precedence over another group and removes to select one group of discriminant function.Fortunately, as long as the high speed and the big data-handling capacity of modern computer are arranged, people just can calculate the density of a lot of groups of functions very simply, and arrangement gained result also identifies the function that those can make obvious separation between each particle type probability histogram curve.
The one group of discriminant function that behaves oneself best that is identified has been arranged, just can generate and distinguish that the storehouse is also with it file.The storehouse must comprise the kind tabulation that is comprised by probability histogram.Each group probability histogram must have the correlation discriminating function of oneself.
In order to debate not unknown particle in the storehouse, the storehouse is loaded into the storer of distinguishing computing machine with distinguishing.Surveying instrument and raw data routine analyzer are measured unknown particle and are extracted aforesaid event descriptor data.
Distinguisher starts from when particle passes laser beam the data measuring and collect unknown particle.It is signal digitalized and extract the event descriptor data from incident that event handler will obtain.Event handler accords with data with event handling and is sent to the ID processor of attempting distinguishing particles then.
The ID processor starts from the value of the event descriptor computational discrimination function of first group of probability histogram from the storehouse.From probability histogram, search or insert probable value for each particle type, and adopt the statistics sorting algorithm to judge that specific particle type produces the probability of these discriminant scores.The result be the one group of probability relevant: p with these first discriminant functions (df, species), df is that the discriminant function group is several in this case in the formula, is that 1-that is to say in this case, it is first group of discriminant function.Respectively organize relevant probability histogram in discriminant function and the storehouse for all, the ID processor repeats this process.
A kind of possible statistics sorting algorithm is described as p with the following manner employing, and (in the formula, df is specific discriminant function for df, probable value group species), and species is a particle type.Each variable grain kind (species) thus probability combine and form a single probable value of this kind:
p(species)＝∑dfW(df)xp(df，species)，
W in the formula (df) is the weight from the probability histogram of discriminant function group df.
Come the distinguishing particles kind by these final probable values of correct interpretation.It is to adopt threshold value that a kind of enforcement is understood.If p (speciess)＞t (species), t in the formula (species) is the threshold value of a certain specific particle type, and all other value all the threshold value than them is little, this particle just is considered to this kind so.If more than one probability is arranged on threshold value separately, if or do not have probability on threshold value, this particle just can not be recognized so.
In this preferred implementing form, instrument of the present invention comprises following combination:
A) the polarization laser of generation beam waist;
B) comprise the optical mount of a plurality of photo-detectors, each photo-detector along around place, and have no concealed ground towards laser light common convergence zone (common region ofregard) with a tight waist;
C) fill the sample chamber of fluid sample to be analyzed;
D) sample chamber is remained on respect on the with a tight waist assigned direction of laser light and remain on device in the common convergence zone of photo-detector;
E) make grain flow in the sample cross the device of laser beam waist;
F) cover light source and optical mount to produce the device of dark outer cover;
G) will convert the device of digital value by the measured light intensity value of detector to;
H) with the device of digital value continuously;
I) based on digitized measurement, judge the device in the light beam when have particle to enter place, common convergence zone;
J) digitizing numerical value is converted to the device of calibration value;
K) extract the device of event descriptor from the event data of digitizing and calibration;
L) from the device of incident descriptor computation discriminant score;
M) device of definition probability histogram, this histogram make and can calculate the probability that specific particle type causes the discriminant score that calculates from measured value;
N) distinguish the device of effective discriminant function.
O) probability histogram and discriminant function are stored in the device of distinguishing in the storehouse, a probability histogram are arranged for each particle type that can be distinguished and each discriminant function;
P) recover the probability histogram of previous storage and the device of discriminant function, can adopt for each and distinguish that particle type and each discriminant function of distinguishing in the storehouse have a probability histogram;
Q) calculate the device of the probability of each particle type in the storehouse for set-point of discriminant function;
R) device that can adopt the probability of distinguishing each particle type of distinguishing in the storehouse to combine; And
S) distinguish the device of unknown particle based on threshold value.