JP2012217382A - Microorganism detecting apparatus - Google Patents
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- Apparatus Associated With Microorganisms And Enzymes (AREA)
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Abstract
Description
本発明は、気体空間に浮遊する菌を回収して、回収中の菌分類を識別する微生物検出装置に関する。
The present invention relates to a microorganism detection apparatus that collects bacteria floating in a gas space and identifies the classification of bacteria being collected.
空中に浮遊する粒子で、その粒子は細菌、ウイルス、バクテリア、原虫、真菌、などの生物や、生物の産物からなる花粉、胞子、酵母、カビなどが上げられるバイオエアロゾルがある。このバイオエアロゾルは、感染性、アレルギー性、毒性の効果を持つため、人間の生活の中での対策が必要である。特に、バイオエアロゾルは、ブドウ球菌や、ＭＲＳＡ（Methicillin Resistant Staphylococcus Aureus;メチシリン耐性黄色ブドウ球菌）などが、院内感染で大きな問題となっている。また、空港・港湾などでは、ＳＡＲＳ（Severe Acute Respiratory Syndrome ;重症急性呼吸器症候群）やバイオテロなどの問題が発生が懸念され、公共機関や交通機関などでは、インフルエンザやバイオテロなどの脅威が心配される。 The particles are floating in the air, and the particles include organisms such as bacteria, viruses, bacteria, protozoa, and fungi, and bioaerosols that can raise pollen, spores, yeast, molds, and the like, which are products of organisms. Since this bioaerosol has infectious, allergic, and toxic effects, it is necessary to take measures in human life. In particular, bioaerosols such as staphylococci and MRSA (Methicillin Resistant Staphylococcus Aureus) are a major problem in nosocomial infections. In addition, there are concerns that SARS (Severe Acute Respiratory Syndrome) and bioterrorism will occur in airports and harbors, and threats such as influenza and bioterrorism are a concern in public institutions and transportation facilities. .
一方、製薬分野においては、無菌室にて無菌環境下での医薬品等の製造が求められる。万が一、微生物が製造中の薬品に混入、増殖すると、その薬品を投与された患者の健康が損なわれる恐れがある。そのため、製薬の製造現場においては微生物の混入は致命的な問題となり、微生物の監視の要求が高まりつつある。 On the other hand, in the pharmaceutical field, it is required to produce pharmaceuticals and the like in a sterile room in a sterile room. In the unlikely event that microorganisms are mixed with or proliferate in the drug being manufactured, the health of the patient receiving the drug may be impaired. Therefore, contamination of microorganisms is a fatal problem at pharmaceutical manufacturing sites, and the demand for monitoring microorganisms is increasing.
このような環境に対応するため、従来では、医薬分野のクリールルーム内で、迅速にバイオエアロゾルをモニタリングするために、レーザ光をバイオエアロゾル中の微生物に照射し、その散乱光を検出することで微生物を検出する光学式パーティクルカウンターが用いられていた。 In order to cope with such an environment, conventionally, in order to quickly monitor bioaerosol in a creel room in the pharmaceutical field, a laser beam is irradiated to microorganisms in the bioaerosol and the scattered light is detected. An optical particle counter that detects microorganisms was used.
また、微生物の特定化を実現するためには、培養法などが用いられている。この培養法は、クリーンルーム内に設置された寒天培地上に落下した微生物を培養槽で培養することで微生物を特定する方法が用いられていた。 Moreover, in order to realize the specification of microorganisms, a culture method or the like is used. In this culturing method, a method of identifying microorganisms by culturing microorganisms dropped on an agar medium installed in a clean room in a culture tank has been used.
そして、特許文献１には、空気中の試料を濃縮するバーチャルインパクタと組み合わせた、エアロゾル収集機により試料を収集し、基板の表面に濃縮した試料を、慣性衝突、超音波付着などで付着させ、レーザを照射して、ラマン散乱光子を発生させ、細菌、ウイルス、原生動物などの脅威物質を識別することが記載されている。 In Patent Document 1, a sample is collected by an aerosol collector combined with a virtual impactor for concentrating the sample in the air, and the sample concentrated on the surface of the substrate is attached by inertial collision, ultrasonic adhesion, etc. It is described that a laser is irradiated to generate Raman scattered photons to identify threat substances such as bacteria, viruses and protozoa.
光学式パーティクルカウンターの場合は、空間に存在する粒子の個数とサイズに関する情報のみが得られ、有機物・無機物の分離や、有機物が微生物由来のものであるか否かを判断することが出来ない。 In the case of an optical particle counter, only information on the number and size of particles present in the space is obtained, and it is impossible to determine whether organic or inorganic substances are separated or whether the organic substances are derived from microorganisms.
一方で、培養法による微生物の特定方法は、微生物の特定を行なうことはできるが、微生物の培養に数十時間を要するため迅速性を有さない。
また、特許文献１における脅威物質を検出および識別するシステムにおいては、試料を周囲環境から、バーチャルインパクタと組み合わせたエアロゾル収集機によって資料を収集し、基板の表面に濃縮した試料を付着させる付着手段と、試料にレーザ光を照射して、ラマン散乱光を発生させて、試料物質を識別する方法が開示されているが、収集する環境空気中に混在する微生物に由来する有機物と、無機物とを分離計測する手段がなく、測定が必要な物質を特定することが困難であって、短時間に計測を行なうことが困難であった。
On the other hand, the method for identifying microorganisms by the culture method can identify microorganisms, but does not have rapidity because it requires several tens of hours to culture microorganisms.
In addition, in the system for detecting and identifying a threat substance in Patent Document 1, a sample is collected from an ambient environment by an aerosol collector combined with a virtual impactor, and attachment means for attaching the concentrated sample to the surface of the substrate is provided. Although a method for identifying sample material by irradiating a sample with laser light and generating Raman scattered light is disclosed, organic substances derived from microorganisms mixed in environmental air to be collected are separated from inorganic substances There is no means for measurement, and it is difficult to specify a substance that needs to be measured, and it is difficult to perform measurement in a short time.
さらに、ラマン散乱は、照射した光に対して非常に小さいため、得られるラマン散乱による分光信号は非常に小さなものになる。このため、数μｍ程度の微生物は、１つの単位で、特定することができない。 Furthermore, since Raman scattering is very small with respect to the irradiated light, the obtained spectral signal by Raman scattering becomes very small. For this reason, a microorganism of about several μm cannot be specified in one unit.
本発明は上記事情に鑑みてなされたものであり、その目的とするところは、バイオクリーンルーム内などの環境空気中に含まれる浮遊微生物を収集し、菌属レベルでの微生物の特定化を、迅速に行なう、微生物検出計測を提供することにある。 The present invention has been made in view of the above circumstances, and the object of the present invention is to collect floating microorganisms contained in environmental air such as in a bioclean room and quickly specify microorganisms at the genus level. It is to provide a microorganism detection measurement to be performed.
本発明に係る気体空間中に浮遊する微生物を回収して、微生物の特定をする微生物検出装置は、計測空間の気体を吸引して含有する微粒子を濃縮する微粒子濃縮手段と、微粒子濃縮手段による濃縮微粒子を付着させる基材と、基材上の前記濃縮微粒子に紫外線を照射する紫外線照射手段と、紫外線照射手段により濃縮微粒子から発する蛍光を、蛍光位置の情報で捕らえる蛍光位置検出手段と、蛍光位置検出手段で得た蛍光を発する微粒子にレーザビームを照射するレーザ照射手段と、レーザ照射手段によって、蛍光を発する微粒子からのラマン散乱光を分光する分光手段と、分光手段による分光を検出する分光検出手段と、微生物の種類ごとのラマンスペクトル情報を格納する基準微生物情報格納手段と、分光検出手段で得たラマンスペクトルと基準微生物情報格納手段内のラマンスペクトル情報を比較して、微生物を特定する手段とを有している。 A microorganism detecting apparatus for collecting microorganisms floating in a gas space and identifying microorganisms according to the present invention includes a fine particle concentrating means for concentrating fine particles contained by sucking the gas in the measurement space, and a concentration by the fine particle concentrating means. A substrate to which fine particles are attached, an ultraviolet irradiation means for irradiating the concentrated fine particles on the substrate with ultraviolet rays, a fluorescence position detecting means for capturing fluorescence emitted from the concentrated fine particles by the ultraviolet irradiation means by information on the fluorescence position, and a fluorescent position Laser irradiation means for irradiating a laser beam to the fluorescent particles obtained by the detection means, a spectral means for dispersing Raman scattered light from the fluorescent particles by the laser irradiation means, and spectral detection for detecting the spectrum by the spectral means Means, reference microorganism information storage means for storing Raman spectrum information for each type of microorganism, and Raman spectrum obtained by the spectroscopic detection means And by comparing the Raman spectral information of the reference microorganisms information storage in means, and a means for identifying a microorganism.
この装置では、環境空間の気中の浮遊する微生物を迅速に検査するために、微粒子濃縮手段により、環境空気を吸引して、吸引した微生物を含む微粒子を濃縮する。微粒子濃縮手段としては、フィルター採取やインパクター法がある。インパクター法では、カスケードインパクター法やバーチャルインパクター法を利用することができる。 In this apparatus, in order to quickly test microorganisms floating in the air in the environment space, the ambient air is sucked by the particulate concentration means to concentrate the particulates containing the sucked microorganisms. As a means for concentrating fine particles, there are a filter collection and an impactor method. In the impactor method, a cascade impactor method or a virtual impactor method can be used.
そして、空気中から回収して濃縮した微粒子を、測定のための基材に付着させる。基材への付着方法としては、採取したフィルターごと載置しても良いし、衝突付着や超音波付着など、様々な方法が利用できる。 Then, the fine particles collected and concentrated from the air are attached to the substrate for measurement. As a method for attaching to the substrate, the collected filter may be placed together, or various methods such as collision attachment and ultrasonic attachment can be used.
次に、採取した濃縮微粒子には、有機物と無機物が混在しており、微生物（細菌）は有機物であるため、有機物の特定を行なう。有機物は、一般的に紫外線を照射すると蛍光を発するが、無機物は蛍光を発することがない。本発明では、紫外線照射手段として、例えば、紫外線ＬＥＤをリング状に配列し、ＬＥＤはリングの中心に向かって傾斜して配置して、紫外線発光がリングの中央付近を照らすようなものを用いると良い。そして、有機物からの蛍光を像として捕らえ、どの位置に有機物が存在しているかを把握できるようにするため、蛍光位置検出手段は、基材上の濃縮微粒子の像を、結像光学系により画像取得部の例えばＣＣＤカメラ上に結像するような画像情報検出手段を有すると良い。 Next, since the collected concentrated fine particles contain both organic and inorganic substances and microorganisms (bacteria) are organic substances, the organic substances are specified. Organic substances generally emit fluorescence when irradiated with ultraviolet rays, but inorganic substances do not emit fluorescence. In the present invention, as the ultraviolet irradiation means, for example, an ultraviolet LED is arranged in a ring shape, the LED is arranged to be inclined toward the center of the ring, and an ultraviolet light emission illuminates the vicinity of the center of the ring. good. Then, in order to capture the fluorescence from the organic substance as an image so that the position where the organic substance is present can be grasped, the fluorescence position detecting means uses the imaging optical system to generate an image of the concentrated fine particles on the substrate. It is preferable to have image information detection means that forms an image on, for example, a CCD camera of the acquisition unit.
基材上の有機物の位置が特定できたところで、その有機物の１つ１つ別々に、レーザ照射手段によってレーザビームを照射し、そこから発生するラマン散乱光を計測する。照射するレーザビームは、紫外線から近赤外線域から選ばれるレーザ発振器を利用し、複数の波長を用意しておくこともできる。レーザの種類としては、例えば、Ａｒ＋レーザ、ＹＡＧレーザ第二高調波、半導体レーザなど、が利用できる。そして、ラマン散乱光は、回折格子などの分光手段によって分光されたラマンスペクトルは、ＣＣＤカメラなどの分光検出手段によって取り込まれ、基準微生物情報格納手段としてパソコンなどに予め格納されている、微生物の種類ごとの指紋情報とも言えるラマンスペクトルと比較を行い、微生物の種類の特定をする。微生物の種類としては、クリーンルーム内で特に監視が必要とされている、枯草菌、大腸菌、Micorococcus luterus やMicorococcus lylaeなどの人の常在菌、ブドウ球菌、Saccharomyces cerevisiae などの一般的な酵母、カビが挙げられる。 When the position of the organic matter on the substrate has been identified, each of the organic matter is separately irradiated with a laser beam by the laser irradiation means, and the Raman scattered light generated therefrom is measured. The laser beam to be irradiated can be prepared with a plurality of wavelengths by using a laser oscillator selected from the ultraviolet to the near infrared region. As the type of laser, for example, Ar + laser, YAG laser second harmonic, semiconductor laser, and the like can be used. The Raman scattered light is scattered by a spectral means such as a diffraction grating, and the Raman spectrum is taken in by a spectral detection means such as a CCD camera and stored in a personal computer or the like in advance as a reference microorganism information storage means. Comparison with the Raman spectrum, which can be said to be fingerprint information for each, identifies the type of microorganism. As for the types of microorganisms, there are common yeasts such as Bacillus subtilis, Escherichia coli, Micorococcus luterus and Micorococcus lylae, staphylococci, and common yeasts such as Saccharomyces cerevisiae and molds that are particularly required to be monitored in a clean room. Can be mentioned.
また、本発明においては、レーザビームを基材上の微粒子に照射する光軸であって、基材に垂直な光軸上に４５度に傾けて光学基板を設け、光学基板が蛍光を透過し、レーザビーム及び前記ラマン散乱光を反射するようにしても良い。 In the present invention, the optical axis for irradiating the fine particles on the base material with the laser beam is provided at an angle of 45 degrees on the optical axis perpendicular to the base material, and the optical base plate transmits fluorescence. The laser beam and the Raman scattered light may be reflected.
また、基材は可撓性のシート状からなり、ロール上に巻かれたシート送り出し部とシート巻取り部を有する構成にすると良い。
そして、可撓性のシート状の基材をシート送り出し部とシート巻取り部によって移動させ、基材上の濃縮微粒子に対して、蛍光位置検出手段及びレーザ照射手段の位置に合わせるようにしても良いし、基材上の濃縮微粒子位置に対して、蛍光位置検出手段及びレーザ照射手段を移動して、位置合わせを行なうようにしても良い。
Further, the substrate is preferably made of a flexible sheet and has a sheet feeding part and a sheet winding part wound on a roll.
Then, the flexible sheet-like base material is moved by the sheet feeding portion and the sheet winding portion so that the concentrated fine particles on the base material are aligned with the positions of the fluorescence position detecting means and the laser irradiation means. Alternatively, the position may be adjusted by moving the fluorescence position detection means and the laser irradiation means with respect to the concentrated fine particle position on the substrate.
本発明によれば、空気中に含まれている微粒子や微生物のうち、有機物のみを特定し、有機物のみに対象を絞って、ラマン分光測定を行なうことができ、菌属レベルでの微生物として、枯草菌、大腸菌、ヒトの身体に存在する常在菌、ブドウ球菌、真菌、酵母、カビといった約７種類の分類を特定することが可能となる。 According to the present invention, among the fine particles and microorganisms contained in the air, only the organic matter can be specified, and only the organic matter can be targeted, and Raman spectroscopic measurement can be performed. It is possible to specify about seven types of classifications such as Bacillus subtilis, Escherichia coli, resident bacteria present in the human body, staphylococci, fungi, yeast, and mold.
医薬品や化粧品、食品、飲料の製造・加工・包装・検査工程、医療施設、遺伝子実験施設などで使用するバイオクリーンルームは、空気中の浮遊微生物を制御・管理しており、これら微生物について、消毒・殺菌・滅菌する必要が生じるが、その菌属を把握できることにより、バイオクリーンルーム内などの環境汚染源の特定化が可能とある。例えば、枯草菌、ブドウ球菌等は外部由来からの汚染、カビなどは空調、大腸菌や真菌などは作業者由来の菌として考えることができるため、適切な対策を講じることが可能となる。 Bioclean rooms used in the manufacturing, processing, packaging, and inspection processes of pharmaceuticals, cosmetics, foods and beverages, medical facilities, genetic laboratory facilities, etc. control and manage airborne microorganisms. Although it is necessary to sterilize and sterilize, it is possible to identify the environmental pollution source in the bio clean room by being able to grasp the genus of the fungus. For example, Bacillus subtilis, staphylococci, and the like can be considered as contamination from the outside, molds and the like can be considered as air conditioning, and Escherichia coli and fungi can be considered as bacteria derived from workers, so that appropriate measures can be taken.
このような、バイオ環境の把握を、迅速かつ適確に行なうことができるので、製造対象の医薬品や食品などへの微生物の混入を抑制するこができる。 Such grasping of the bioenvironment can be performed quickly and accurately, so that the mixing of microorganisms into the pharmaceutical or food to be manufactured can be suppressed.
以下、本発明の実施の形態について、図面を用いて説明する。
図１は、本発明に係る微生物検出と特定を行なう装置構成図である。そして、図２は、本発明に係る微生物検出と特定のフロー図である。
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a configuration diagram of an apparatus for performing microorganism detection and identification according to the present invention. FIG. 2 is a flowchart of microorganism detection and specific processing according to the present invention.
図１における本発明に係る微生物検出と特定を行なう微生物特定化検出器においては、微粒子濃縮部１０と、有機物・無機物分離部２０と、ラマン分光による微生物の特定部３０と、シート移動部４０とから構成されている。 In the microorganism-specification detector that performs the microorganism detection and identification according to the present invention in FIG. 1, the fine particle concentration unit 10, the organic / inorganic separation unit 20, the microorganism identification unit 30 by Raman spectroscopy, and the sheet moving unit 40 It is composed of
これらの構成において、図１と図２により、その詳細について説明する。
例えば、今回の発明が適用されるバイオクリーンルームの場合、非常にクリーンな環境であることから微粒子の総数が限られ、生物由来の微生物の数も限られることになる。このような環境の中でも、数多くの微生物をサンプリングするため、バイオクリーンルーム内の、微生物を含む微粒子が浮遊する多くの空気を吸引し、微粒子と空気の分離を行なうことで、空気中に含まれる微生物を高い確率で集塵することが可能となる。
Details of these configurations will be described with reference to FIGS.
For example, in the case of a bioclean room to which the present invention is applied, since the environment is very clean, the total number of fine particles is limited, and the number of organism-derived microorganisms is also limited. Even in such an environment, in order to sample a large number of microorganisms, the microorganisms contained in the air are separated by drawing a large amount of air in the bioclean room where fine particles containing microorganisms are suspended and separating the particles from the air. Can be collected with high probability.
そこで、図１において、本発明による微粒子濃縮部１０では、測定環境中の空気１２を、微生物を含む微粒子と空気との分離を行なうバーチャルインパクタ１１で構成している。先ず、測定環境中の空気をバーチャルインパクタ１１で吸引し、微生物を含む微粒子と空気を分離して、微生物を含む濃縮空気１３を取り出す。バーチャルインパクタ１１から取り出した微生物を含む濃縮空気１３は、バーチャルインパクタ１１の取り出し部近傍に設けられた、シート４１上に吹き付けて、微生物を含む微粒子をシート４１上に固定化する。 Therefore, in FIG. 1, in the fine particle concentrating unit 10 according to the present invention, the air 12 in the measurement environment is constituted by a virtual impactor 11 that separates fine particles containing microorganisms from air. First, air in the measurement environment is sucked by the virtual impactor 11, the microparticles containing microorganisms are separated from the air, and the concentrated air 13 containing microorganisms is taken out. The concentrated air 13 containing microorganisms taken out from the virtual impactor 11 is sprayed onto the sheet 41 provided in the vicinity of the take-out portion of the virtual impactor 11 to immobilize fine particles containing microorganisms on the sheet 41.
シート４１は、未使用のシート４１が巻かれているシート送り出し部４２と、シート巻取り部４３で構成するシート移動部４０によって、シート送り出し部４２からシート４１を、微粒子濃縮部１０と、次に述べる有機物・無機物分離部２０に、図示しないシート移動手段によって、順次送られるように移動し、その後、シート巻取り部４３に巻取り回収される。 The sheet 41 is transferred from the sheet feeding unit 42 to the fine particle concentrating unit 10 by the sheet feeding unit 42 in which the unused sheet 41 is wound and the sheet moving unit 40 configured by the sheet winding unit 43. The sheet is moved to the organic / inorganic separation unit 20 described in the above by a sheet moving unit (not shown) so as to be sequentially fed, and then wound and collected by the sheet winding unit 43.
このように、微粒子濃縮部１０においては、図２のフロー図で示す、Ｓｔｅｐ１の微生物が含まれる空気をバーチャルインパクタ１１で濃縮する工程と、Ｓｔｅｐ２のシートに吹き付けた微生物を含む微粒子を固定化する工程とを行なう。 As described above, in the fine particle concentrating unit 10, the step of concentrating the air containing the Step 1 microorganisms with the virtual impactor 11 shown in the flowchart of FIG. 2 and the fine particles containing the microorganisms sprayed on the Step 2 sheet are immobilized. Process.
次に、バーチャルインパクタ１１で濃縮し、シート４１に固定化した微生物を含む微粒子中の有機物と無機物の分離について説明する。
図１において、有機物・無機物分離部２０は、レンズ２１ａ，２１ｂ、紫外線照明２２、蛍光検出用ＣＣＤカメラ２３、光学基板２４、有機物位置分析演算部２５で構成されている。
Next, separation of an organic substance and an inorganic substance in microparticles containing microorganisms concentrated by the virtual impactor 11 and immobilized on the sheet 41 will be described.
In FIG. 1, the organic substance / inorganic substance separating unit 20 includes lenses 21 a and 21 b, ultraviolet illumination 22, a fluorescence detection CCD camera 23, an optical substrate 24, and an organic substance position analysis calculation unit 25.
先ず、シート４１上に固定化した微生物を含む微粒子を、有機物・無機物分析部２０のレンズ２１ａの光軸上に、シート移動部４０によりシート４１を動かして移動する。このように、シート４１を動かして、微生物を含む微粒子の固定化箇所が、レンズ２１ａと、レンズ２１ｂにより、蛍光検出用ＣＣＤカメラ２３に結像するように配置する。 First, fine particles containing microorganisms immobilized on the sheet 41 are moved by moving the sheet 41 by the sheet moving unit 40 on the optical axis of the lens 21 a of the organic / inorganic substance analyzing unit 20. In this manner, the sheet 41 is moved and arranged so that the microparticle-containing immobilization site is imaged on the fluorescence detection CCD camera 23 by the lens 21a and the lens 21b.
そして、レンズ２１ａのシート４１の配置と反対方向で、レンズ２１ａの中央を除く周囲に、紫外線照明２２を配置する。紫外線照明２２は、例えば、ＬＥＤをリング状に配置し、リングの中央方向にＬＥＤを傾斜することで、中央付近を明るく均一に照明できるようになっている。このＬＥＤは、紫外線照明光が照射されるタイプを用い、この紫外線照明光が、シート４１に固定化した微粒子に照射される。
そして、一般的に、微粒子中の有機物は、紫外線により蛍光を発し、無機物は蛍光を発しないので、有機物から発せられる蛍光を、レンズ２１ａと、その光軸上に配置されているレンズ２１ｂにより、蛍光検出用ＣＣＤカメラ２３のＣＣＤ面に結像するように構成する。
And the ultraviolet illumination 22 is arrange | positioned in the circumference | surroundings except the center of the lens 21a in the opposite direction to arrangement | positioning of the sheet | seat 41 of the lens 21a. The ultraviolet illumination 22 is configured such that, for example, LEDs are arranged in a ring shape, and the LEDs are inclined toward the center of the ring so that the vicinity of the center can be illuminated brightly and uniformly. The LED is of a type that is irradiated with ultraviolet illumination light, and the ultraviolet illumination light is applied to the fine particles fixed to the sheet 41.
In general, the organic matter in the fine particles emits fluorescence by ultraviolet rays, and the inorganic matter does not emit fluorescence. Therefore, the fluorescence emitted from the organic matter is obtained by the lens 21a and the lens 21b disposed on the optical axis thereof. An image is formed on the CCD surface of the CCD camera 23 for fluorescence detection.
そして、蛍光検出用ＣＣＤカメラ２３で得られた画像情報は、有機物位置分析演算部２５に送られ、有機物の位置情報として処理され、有機物位置分析演算部２５内のメモリに格納される。 The image information obtained by the fluorescence detection CCD camera 23 is sent to the organic matter position analysis calculation unit 25, processed as the position information of the organic matter, and stored in the memory in the organic matter position analysis calculation unit 25.
また、図１において、有機物からの蛍光２６は、レンズ２１ｂと蛍光検出用ＣＣＤカメラ２３に入光する前に配置されている光学基板２４を通過している。この光学基板２４は、後述するラマン分光による菌の特定部３０からの光源を、４５度で反射させて、シート４１に固定化した微粒子に照射するために設置が必要である。このため、有機物・無機物分離部２０としては、光学基板２４に対して、有機物からの蛍光２６が、４５度で入光した場合に、蛍光検出用ＣＣＤカメラ２３にて検出できる光量が得られる程度に透過すれば良い。この場合には、有機物からの蛍光２６に対する光学処理を、光学基板２４に施す必要は必ずしもないが、光学基板２４による表面反射を抑えたい場合や、光学基板２４を透過して蛍光検出用ＣＣＤカメラ２３に到達する光量が少ない場合には、光学基板２４表面に、４５度入射に対する無反射コートを施すと良い。 In FIG. 1, the fluorescence 26 from the organic substance passes through the optical substrate 24 arranged before entering the lens 21b and the fluorescence detection CCD camera 23. The optical substrate 24 needs to be installed in order to irradiate the fine particles fixed on the sheet 41 by reflecting a light source from the bacteria identifying unit 30 by Raman spectroscopy, which will be described later, at 45 degrees. For this reason, as the organic / inorganic separation unit 20, when the fluorescence 26 from the organic material enters the optical substrate 24 at 45 degrees, the amount of light that can be detected by the fluorescence detection CCD camera 23 is obtained. It only has to pass through. In this case, it is not always necessary to apply optical processing to the fluorescent light 26 from the organic matter to the optical substrate 24. However, when it is desired to suppress the surface reflection by the optical substrate 24, or to transmit the optical substrate 24 and detect the fluorescence by the CCD camera. When the amount of light reaching 23 is small, a non-reflective coating for 45-degree incidence may be applied to the surface of the optical substrate 24.
有機物・無機物分析部２０における動作は、図２において、Ｓｔｅｐ３〜Ｓｔｅｐ５に示されている。すなわち、Ｓｔｅｐ３による、シート４１を移動し、微生物を含む微粒子の固定化部をレンズの検出位置に合わせ、次いで、Ｓｔｅｐ４による、紫外線照明をシート４１に照射し、有機物からの蛍光を蛍光検出受光部で検出して、Ｓｔｅｐ５として、蛍光の有無から有機物と無機物を分離し、有機物の位置を有機物位置分析検算部で演算処理するようにする。 The operation in the organic matter / inorganic matter analyzing unit 20 is shown in Step 3 to Step 5 in FIG. That is, the sheet 41 is moved by Step 3, the microparticle-containing immobilization part is moved to the detection position of the lens, and then, the UV light is irradiated to the sheet 41 by Step 4, and the fluorescence from the organic matter is detected by the fluorescence detection light receiving part. In Step 5, the organic substance and the inorganic substance are separated from the presence or absence of fluorescence, and the position of the organic substance is calculated by the organic substance position analysis / calculation unit.
シート４１に固定化された微生物を含む微粒子において、微生物の確立が高い有機物を特定したので、その有機物に励起光であるレーザ光を照射して、発生するラマン散乱を捕らえて、微生物を特定するための装置構成を、図１で説明する。 In the microparticles containing microorganisms immobilized on the sheet 41, an organic substance having a high establishment of microorganisms is identified. Therefore, the organic substance is irradiated with laser light as excitation light, and the generated Raman scattering is captured to identify the microorganisms. An apparatus configuration for this will be described with reference to FIG.
図１でのラマン分光による微生物の特定部３０は、励起用のレーザ光源３１と、励起用のレーザ光源３１から照射するレーザビーム３２と、レーザビーム３２の光軸調整用の４５度反射ミラー３３ａ，３３ｂと、レーザビーム３２が、有機物・無機物分離部２０における光学基板２４で反射して、レンズ２１ａにより集光されて、シート４１上の有機物に照射されることで発生するラマン散乱光３４を、光学基板２４で反射し、４５度反射ミラー３３ｂを透過したラマン散乱光３４を分光する回折格子３５と、回折格子３５で分光したラマンスペクトルを入光する分光検出用ＣＣＤカメラ３６により構成する。そして、分光検出用ＣＣＤカメラ３６で得られた情報は、ラマンスペクトルを解析する分光分析演算部３７に取り込まれるようになっている。 The microorganism identifying unit 30 by Raman spectroscopy in FIG. 1 includes an excitation laser light source 31, a laser beam 32 irradiated from the excitation laser light source 31, and a 45-degree reflection mirror 33 a for adjusting the optical axis of the laser beam 32. , 33b, and the laser beam 32 reflected by the optical substrate 24 in the organic / inorganic separation unit 20, condensed by the lens 21a, and irradiated with the organic matter on the sheet 41. A diffraction grating 35 that splits the Raman scattered light 34 reflected by the optical substrate 24 and transmitted through the 45-degree reflection mirror 33b, and a CCD camera 36 for spectral detection that receives the Raman spectrum split by the diffraction grating 35. The information obtained by the spectral detection CCD camera 36 is taken into a spectral analysis calculation unit 37 for analyzing a Raman spectrum.
また、４５度反射ミラー３３ｂは、レーザビーム３２の波長を、４５度の入射角で全反射し、ラマン散乱光３４を通過するコーティングが施されていることが好ましく、光学基板２４には、レーザビーム３２の波長とラマン散乱光３４の両方が全反射するコーティングが施されていることが好ましい。そして、ラマン散乱光３４を分光する回折格子３５にラマン散乱光３４が当たる前には、４５度反射ミラー３３ｂを透過した、励起光であるレーザビーム３２と同じ波長の光として散乱するレイリー散乱光などのラマン散乱光３４以外の光をカットするフィルター３８を設けても良い。 The 45-degree reflecting mirror 33b is preferably provided with a coating that totally reflects the wavelength of the laser beam 32 at an incident angle of 45 degrees and passes the Raman scattered light 34. It is preferable to provide a coating that totally reflects both the wavelength of the beam 32 and the Raman scattered light 34. Then, before the Raman scattered light 34 hits the diffraction grating 35 that splits the Raman scattered light 34, the Rayleigh scattered light that has passed through the 45-degree reflection mirror 33b and is scattered as light having the same wavelength as the laser beam 32 that is excitation light. A filter 38 for cutting light other than the Raman scattered light 34 such as the above may be provided.
さらに、レーザビーム３２は、図２でのＳｔｅｐ５において得た、シート４１上の有機物の位置情報を基にして、順次、有機物にレーザ光が照射されるように、有機物・無機物分析部２０を含むラマン分光による微生物の特定部３０の装置全体を、図示しない移動装置で動かしても良いし、レンズ２１ａと光軸調整用の４５度反射ミラー３３ａ，３３ｂを動かすようにしても良い。 Further, the laser beam 32 includes an organic matter / inorganic matter analyzing unit 20 so that the organic matter is sequentially irradiated with laser light based on the position information of the organic matter on the sheet 41 obtained in Step 5 in FIG. The entire device of the microorganism identifying unit 30 by Raman spectroscopy may be moved by a moving device (not shown), or the lens 21a and the 45-degree reflecting mirrors 33a and 33b for adjusting the optical axis may be moved.
シート４１上の有機物に励起用レーザビーム３２を照射してラマン散乱光３４を得る動作を、図２のＳｔｅｐ６〜Ｓｔｅｐ９により説明する。
Ｓｔｅｐ５で、蛍光の有無から有機物と無機物を分離し、有機物の位置を有機物位置分析検算部で演算処理された情報に対して、Ｓｔｅｐ６として、有機物（微生物）にレーザビーム３２を照射する。この時、レーザビーム３２を最初に照射する有機物を選び、その有機物にレーザビーム３２が照射されるように、シート４１を駆動するか、あるいは、図１での有機物・無機物分析部２０を含むラマン分光による微生物の特定部３０の装置全体を動かすか、レンズ２１ａと光軸調整用の４５度反射ミラー３３ａ，３３ｂを動かすようにする。
The operation of obtaining the Raman scattered light 34 by irradiating the organic matter on the sheet 41 with the excitation laser beam 32 will be described with reference to Step 6 to Step 9 in FIG.
In Step 5, the organic substance and the inorganic substance are separated from the presence or absence of fluorescence, and the organic substance (microorganism) is irradiated with the laser beam 32 as Step 6 on the information obtained by calculating the position of the organic substance in the organic substance position analysis / calculation unit. At this time, an organic material to be first irradiated with the laser beam 32 is selected, and the sheet 41 is driven so that the organic material is irradiated with the laser beam 32, or the Raman including the organic / inorganic material analyzing unit 20 in FIG. The entire device of the microorganism identification unit 30 by spectroscopy is moved, or the lens 21a and the 45-degree reflection mirrors 33a and 33b for adjusting the optical axis are moved.
次に、Ｓｔｅｐ7として、ラマン分光特性を分光検出受光部（分光検出用ＣＣＤカメラ３６）で検出し、Ｓｔｅｐ８で、分光分析演算部３７で波形を解析する。即ち、シート４１上の有機物に励起光としてレーザビーム３２を照射したことで生じる、ラマン散乱光３４が、光学基板２４で反射し、４５度反射ミラー３３ｂを透過してラマン分光検出用ＣＣＤカメラ３６で受光し、分光分析演算部３７でラマンスペクトルを、例えば、図３のように、縦軸がラマン散乱強度（Ｉｎｔｅｎｓｉｔｉｙ）で横軸がラマンシフト（ｃｍ-1）として示す。 Next, as Step 7, the Raman spectral characteristics are detected by the spectral detection light receiving unit (spectral detection CCD camera 36), and at Step 8, the spectral analysis calculation unit 37 analyzes the waveform. That is, the Raman scattered light 34 generated by irradiating the organic substance on the sheet 41 with the laser beam 32 as the excitation light is reflected by the optical substrate 24 and transmitted through the 45-degree reflecting mirror 33b to be detected by the CCD camera 36 for Raman spectroscopy detection. The spectral analysis calculation unit 37 shows the Raman spectrum, for example, as shown in FIG. 3, where the vertical axis indicates the Raman scattering intensity (Intensity) and the horizontal axis indicates the Raman shift (cm −1 ).
そして、Ｓｔｅｐ９で、事前に格納している分光分析演算部３７内のデータベースの微生物と比較し、微生物を特定する。そして、データベースの微生物としては、枯草菌、大腸菌、ヒトの身体に存在する常在菌、ブドウ球菌、真菌、酵母、カビといった約７種類の菌属レベルでの微生物を分類可能な情報を有していることが好ましい。 Then, in Step 9, the microorganism is identified by comparing with the microorganism in the database in the spectroscopic analysis calculation unit 37 stored in advance. The database contains information that can be used to classify microorganisms at about seven types of fungi such as Bacillus subtilis, Escherichia coli, resident bacteria present in the human body, staphylococci, fungi, yeast, and mold. It is preferable.
ここで、分子内と分子間相互作用は、分子構造ごとの固有の基準振動の周波数および形態を有している。このため、ラマン効果において観察される周波数、強度および分極状態を分析することにより、分子構造の情報が得られる。すなわち、微生物の種類ごとに固有な分子構造を有しており、ラマン効果によって観察される周波数、強度、分極状態が微生物の種類によって変化するため、これらを微生物の指紋情報として得ることができる。大腸菌、枯草菌、乳酸菌を例として、それぞれの菌のラマンスペクトルを、図３に示す。図３においては、特に四角で囲んだ２箇所について、菌の種類ごとに異なった波形を示すことがわかる。このような菌種の情報を、測定した有機物からのラマン散乱光３４によるラマンスペクトルと比較して、微生物の有無と、微生物であった場合はどの種類の菌であるかの特定を行なう。 Here, the intramolecular and intermolecular interactions have a unique frequency and form of the reference vibration for each molecular structure. For this reason, molecular structure information can be obtained by analyzing the frequency, intensity, and polarization state observed in the Raman effect. That is, it has a unique molecular structure for each type of microorganism, and the frequency, intensity, and polarization state observed by the Raman effect vary depending on the type of microorganism, so that these can be obtained as fingerprint information of the microorganism. Taking Escherichia coli, Bacillus subtilis, and lactic acid bacteria as examples, the Raman spectrum of each bacterium is shown in FIG. In FIG. 3, it can be seen that different waveforms are shown for each type of bacteria, particularly at two places surrounded by a square. Such information on the species is compared with the Raman spectrum by the measured Raman scattered light 34 from the organic matter, and the presence or absence of microorganisms and, if they are microorganisms, the type of bacteria is specified.
以上のようにして、空気中から採取した微粒子中の有機物を検出し、さらに、その有機物が微生物（菌）であるかも含め、菌の種類の特定までを行なうことが可能である。
そして、シート４１に固定化された微生物を含む微粒子中の有機物が、複数個存在している場合には、図２におけるＳｔｅｐ１０〜Ｓｔｅｐ１２を実施する。先ず、Ｓｔｅｐ１０においては、有機物位置分析用計算器２５のメモリに確保された有機物の位置情報に基づいて、未だラマン散乱を測定していない別の有機物の存在有無を判断し、測定を行なっていない別の有機物がある場合には、Ｓｔｅｐ１１として、次の有機物の位置にビーム照射位置を合わせる動作を、シート４１を駆動するか、あるいは、図１での有機物・無機物分析部２０を含むラマン分光による微生物の特定部３０の装置全体を動かすか、レンズ２１ａと光軸調整用の４５度反射ミラー３３ａ，３３ｂを動かすようにして行なう。そして、Ｓｔｅｐ６〜Ｓｔｅｐ９を同様にして実施する。
As described above, it is possible to detect the organic matter in the fine particles collected from the air, and further to identify the type of bacteria, including whether the organic matter is a microorganism (fungus).
Then, when there are a plurality of organic substances in the microparticles containing microorganisms immobilized on the sheet 41, Steps 10 to 12 in FIG. 2 are performed. First, in Step 10, based on the position information of the organic matter secured in the memory of the organic matter position analysis calculator 25, the presence / absence of another organic matter that has not yet been measured for Raman scattering is determined and measurement is not performed. When there is another organic substance, as Step 11, the operation of aligning the beam irradiation position with the position of the next organic substance is driven by the sheet 41 or by Raman spectroscopy including the organic substance / inorganic substance analyzing unit 20 in FIG. The entire device of the microorganism identification unit 30 is moved, or the lens 21a and the 45-degree reflection mirrors 33a and 33b for adjusting the optical axis are moved. Then, Step 6 to Step 9 are performed in the same manner.
また、Ｓｔｅｐ１０で、ラマン散乱を測定していない有機物の存在が無かった場合には、Ｓｔｅｐ１２として、シート移動部４０により、シート４１を送って、微粒子濃縮部１０で、シート４１の次の場所に固定化した微生物を含む微粒子の位置に、有機物・無機物分析部２０をＳｔｅｐ３と同様の手順で合わせ、Ｓｔｅｐ３〜Ｓｔｅｐ９を同様にして実施する。 If there is no organic substance whose Raman scattering has not been measured at Step 10, the sheet moving unit 40 sends the sheet 41 as Step 12, and the particulate concentration unit 10 moves to the next location of the sheet 41. The organic substance / inorganic substance analyzing unit 20 is aligned with the position of the microparticles including the immobilized microorganisms in the same procedure as in Step 3, and Steps 3 to 9 are performed in the same manner.
本実施例においては、微粒子濃縮部１０によりシート４１上に固定化した微生物を含む微粒子を、ラマン分光による微生物の特定部３０を含む有機物・無機物分析部２０による測定位置に、シート移動部４０によりシート４１を移動するようにしているが、本発明は、これに限定するものでは無く、微粒子濃縮部１０やラマン分光による微生物の特定部３０を含む有機物・無機物分析部２０を移動させるような構成として、微粒子濃縮部１０で微生物を含む微粒子を固定化した位置へ、微粒子濃縮部１０が次ぎのシート４１上の次の固定化位置に移動してから、あるいは移動に合わせて、ラマン分光による微生物の特定部３０を含む有機物・無機物分析部２０を動かして、測定を行なうようにしても良い。 In the present embodiment, fine particles containing microorganisms immobilized on the sheet 41 by the fine particle concentrating unit 10 are measured by the sheet moving unit 40 at the measurement position by the organic / inorganic substance analyzing unit 20 including the microorganism specifying unit 30 by Raman spectroscopy. Although the sheet 41 is moved, the present invention is not limited to this, and the configuration is such that the organic matter / inorganic matter analyzing unit 20 including the fine particle concentrating unit 10 and the microorganism identifying unit 30 by Raman spectroscopy is moved. As described above, after the fine particle concentration unit 10 moves to the next fixing position on the next sheet 41 to the position where the fine particle containing microorganisms are fixed by the fine particle concentration unit 10, the microorganisms by Raman spectroscopy are used. The organic / inorganic analysis unit 20 including the specific unit 30 may be moved to perform measurement.
ラマン効果により発生するラマン散乱光は、照射する励起用のレーザビーム３２に対して、非常の弱い光である。このために、得られるラマン散乱光３４からのラマンスペクトルとしての分光信号は、非常に小さい。このことから、ラマン散乱光３４によって、数μｍ程度の微生物（細菌）を、１個の単位で特定することとは難しい。 The Raman scattered light generated by the Raman effect is very weak with respect to the excitation laser beam 32 to be irradiated. For this reason, the spectral signal as a Raman spectrum from the obtained Raman scattered light 34 is very small. For this reason, it is difficult to specify microorganisms (bacteria) of about several μm in one unit by the Raman scattered light 34.
そこで、本発明での微生物の特定を行なうための一つの方法として、微生物を含む微粒子を固定化するシート４１の表面に、金、銀あるいは銅などの金属ナノ微粒子を吹き付けたものを用いた、表面増強ラマン散乱（Surface Enhanced Raman Scattering ：SERS）を利用することで、微生物１個からのラマン散乱光３４が、大きな信号として得るようにすることができる。 Therefore, as one method for identifying microorganisms in the present invention, the surface of the sheet 41 that immobilizes microparticles containing microorganisms was used by spraying metal nanoparticle such as gold, silver or copper, By using surface enhanced Raman scattering (SERS), the Raman scattered light 34 from one microorganism can be obtained as a large signal.
以上、図面を参照して本発明の実施形態について述べたが、これらは本発明の例示であり、上記以外の様々な構成を採用することもできる。 As mentioned above, although embodiment of this invention was described with reference to drawings, these are the illustrations of this invention, Various structures other than the above are also employable.
１０ 微粒子濃縮部
１１ バーチャルインパクタ
１３ 微生物を含む濃縮空気
２０ 有機物・無機物分離部
２１ａ，２１ｂ レンズ
２２ 紫外線照明
２３ 蛍光検出用ＣＣＤカメラ
２４ 光学基板
２５ 有機物位置分析演算部
２６ 有機物からの蛍光
３０ ラマン分光による微生物の特定部
３１ 励起用のレーザ光源
３２ レーザビーム
３３ａ，３３ｂ ４５度反射ミラー
３４ ラマン散乱光
３５ 回折格子
３６ 分光検出用ＣＣＤカメラ
３７ 分光分析演算部
４０ シート移動部
４１ シート
４２ シート送り出し部
４３ シート巻取り部
DESCRIPTION OF SYMBOLS 10 Fine particle concentration part 11 Virtual impactor 13 Concentrated air containing microorganisms 20 Organic substance and inorganic substance separation part 21a, 21b Lens 22 UV illumination 23 CCD camera for fluorescence detection 24 Optical substrate 25 Organic substance position analysis calculation part 26 Fluorescence from organic substance 30 By Raman spectroscopy Microbe identification unit 31 Excitation laser light source 32 Laser beam 33a, 33b 45 degree reflection mirror 34 Raman scattered light 35 Diffraction grating 36 Spectral detection CCD camera 37 Spectral analysis calculation unit 40 Sheet moving unit 41 Sheet 42 Sheet delivery unit 43 Sheet Winding part
Claims (6)
計測空間の気体を吸引して含有する微粒子を濃縮する微粒子濃縮手段と、
前記微粒子濃縮手段による濃縮微粒子を付着させる基材と、
前記基材上の前記濃縮微粒子に紫外線を照射する紫外線照射手段と、
前記紫外線照射手段により前記濃縮微粒子から発する蛍光を、蛍光位置の情報で捕らえる蛍光位置検出手段と、
前記蛍光位置検出手段で得た蛍光を発する微粒子にレーザビームを照射するレーザ照射手段と、
前記レーザ照射手段によって、前記蛍光を発する微粒子からのラマン散乱光を分光する分光手段と、
前記分光手段による分光を検出する分光検出手段と、
微生物の種類ごとのラマンスペクトル情報を格納する基準微生物情報格納手段と、
前記分光検出手段で得たラマンスペクトルと前記基準微生物情報格納手段内のラマンスペクトル情報を比較して、微生物を特定する手段とを
有することを特徴とする微生物検出装置。
In a detection device that collects microorganisms floating in the gas space and identifies the microorganisms,
Fine particle concentration means for concentrating fine particles contained by sucking the gas in the measurement space;
A base material to which concentrated fine particles by the fine particle concentration means are attached;
Ultraviolet irradiation means for irradiating the concentrated fine particles on the substrate with ultraviolet rays;
Fluorescence position detection means for capturing fluorescence emitted from the concentrated fine particles by the ultraviolet irradiation means with information on fluorescence position;
Laser irradiation means for irradiating the fine particles emitting fluorescence obtained by the fluorescence position detection means with a laser beam;
Spectroscopic means for spectrally dispersing Raman scattered light from the fluorescent fine particles by the laser irradiation means;
Spectral detection means for detecting a spectrum by the spectral means;
Reference microorganism information storage means for storing Raman spectrum information for each type of microorganism;
A microorganism detection apparatus comprising: means for comparing a Raman spectrum obtained by the spectral detection means and Raman spectrum information in the reference microorganism information storage means to identify microorganisms.
2. The microorganism detecting apparatus according to claim 1, wherein the fluorescent position detecting means is means for detecting image information of the image of the concentrated fine particles on the substrate by an imaging optical system.
An optical axis for irradiating the fine particles on the base material with the laser beam, and an optical substrate provided at an angle of 45 degrees on the optical axis perpendicular to the base material, the optical substrate transmitting the fluorescence, The microorganism detection apparatus according to claim 1, wherein the laser beam and the Raman scattered light are reflected.
4. The microorganism detecting apparatus according to claim 1, wherein the base material is formed of a flexible sheet, and has a sheet feeding part and a sheet winding part wound on a roll.
The flexible sheet-like base material is moved by the sheet feeding portion and the sheet winding portion, and the position of the fluorescence position detection means and the laser irradiation means is relative to the concentrated fine particles on the base material. The microorganism detection apparatus according to claim 4, wherein
The microorganism detection according to any one of claims 1 to 3, wherein the fluorescent position detection unit and the laser irradiation unit are moved and aligned with respect to the concentrated fine particle position on the substrate. apparatus.
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Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014140314A (en) * | 2013-01-22 | 2014-08-07 | Azbil Corp | Microbial detection system and microbial detection method |
| WO2014122889A1 (en) * | 2013-02-08 | 2014-08-14 | リオン株式会社 | System for counting viable particles and method for counting viable particles |
| JP2014168442A (en) * | 2013-03-05 | 2014-09-18 | Azbil Corp | Microorganism detection device and microorganism detection method |
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| CN112268886A (en) * | 2020-09-04 | 2021-01-26 | 武汉光谷航天三江激光产业技术研究院有限公司 | Laser rapid detection and disinfection integrated device and method for virus and bacteria |
| CN114324296A (en) * | 2021-12-31 | 2022-04-12 | 海南大学 | Rapid identification method for powdery mildew conidia |
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| KR20220111360A (en) * | 2021-02-02 | 2022-08-09 | (주)미디어에버 | Apparatus for identifying species of microbe in real-time |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0636986A (en) * | 1992-07-14 | 1994-02-10 | Nec Kyushu Ltd | Stepper |
| JP2007524389A (en) * | 2003-06-27 | 2007-08-30 | ケムイメージ コーポレイション | Wide-field method for detecting pathogenic microorganisms |
| JP2007292704A (en) * | 2006-03-29 | 2007-11-08 | Seki Technotron Corp | Method for automatic measurement of foreign substance in injection liquid drug by raman spectrometry, and device therefor |
| US20080192246A1 (en) * | 2004-06-30 | 2008-08-14 | Chemlmage Corporation | Multimodal method for identifying hazardous agents |
| JP2008533448A (en) * | 2005-02-09 | 2008-08-21 | ケムイメージ コーポレイション | System and method for detecting and identifying threat substances |
| WO2009108795A1 (en) * | 2008-02-26 | 2009-09-03 | Battelle Memorial Institute | Biological and chemical microscopic targeting |
| JP2010513847A (en) * | 2006-06-27 | 2010-04-30 | バイオヴィジラント システムズ インコーポレイテッド | Pathogen detection by simultaneous measurement of particle size and fluorescence |
| JP2011058953A (en) * | 2009-09-10 | 2011-03-24 | Olympus Corp | Detector, optical apparatus with the same |
-
2011
- 2011-04-08 JP JP2011086215A patent/JP2012217382A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0636986A (en) * | 1992-07-14 | 1994-02-10 | Nec Kyushu Ltd | Stepper |
| JP2007524389A (en) * | 2003-06-27 | 2007-08-30 | ケムイメージ コーポレイション | Wide-field method for detecting pathogenic microorganisms |
| US20080192246A1 (en) * | 2004-06-30 | 2008-08-14 | Chemlmage Corporation | Multimodal method for identifying hazardous agents |
| JP2008533448A (en) * | 2005-02-09 | 2008-08-21 | ケムイメージ コーポレイション | System and method for detecting and identifying threat substances |
| JP2007292704A (en) * | 2006-03-29 | 2007-11-08 | Seki Technotron Corp | Method for automatic measurement of foreign substance in injection liquid drug by raman spectrometry, and device therefor |
| JP2010513847A (en) * | 2006-06-27 | 2010-04-30 | バイオヴィジラント システムズ インコーポレイテッド | Pathogen detection by simultaneous measurement of particle size and fluorescence |
| WO2009108795A1 (en) * | 2008-02-26 | 2009-09-03 | Battelle Memorial Institute | Biological and chemical microscopic targeting |
| JP2011058953A (en) * | 2009-09-10 | 2011-03-24 | Olympus Corp | Detector, optical apparatus with the same |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014140314A (en) * | 2013-01-22 | 2014-08-07 | Azbil Corp | Microbial detection system and microbial detection method |
| US11215551B2 (en) | 2013-02-08 | 2022-01-04 | Rion Co., Ltd. | Viable particle counting system and viable particle counting method |
| WO2014122889A1 (en) * | 2013-02-08 | 2014-08-14 | リオン株式会社 | System for counting viable particles and method for counting viable particles |
| JP2014153199A (en) * | 2013-02-08 | 2014-08-25 | Rion Co Ltd | Viable particle counting system and viable particle counting method |
| JP2014168442A (en) * | 2013-03-05 | 2014-09-18 | Azbil Corp | Microorganism detection device and microorganism detection method |
| JP2015114161A (en) * | 2013-12-10 | 2015-06-22 | アズビル株式会社 | Particle detecting apparatus, and particle detecting method |
| JP2015139444A (en) * | 2014-01-30 | 2015-08-03 | アズビル株式会社 | Microorganism detection system and microorganism detection method |
| KR20150101649A (en) * | 2014-02-27 | 2015-09-04 | 엘지전자 주식회사 | Airborne microbial measurement apparatus and measurement method |
| JP2017507332A (en) * | 2014-02-27 | 2017-03-16 | エルジー エレクトロニクス インコーポレイティド | Suspended microorganism measuring apparatus and measuring method thereof |
| US10371616B2 (en) | 2014-02-27 | 2019-08-06 | Lg Electronics Inc. | Airborne microbial measurement apparatus and method |
| KR102199814B1 (en) | 2014-02-27 | 2021-01-08 | 엘지전자 주식회사 | Airborne microbial measurement apparatus and measurement method |
| JP2017511487A (en) * | 2014-04-17 | 2017-04-20 | バテル メモリアル インスティチュート | Explosives detector using optical spectroscopy |
| JP2017049150A (en) * | 2015-09-02 | 2017-03-09 | アズビル株式会社 | Method for measuring fluorescent particles |
| CN105628676A (en) * | 2015-12-29 | 2016-06-01 | 北京华泰诺安探测技术有限公司 | Raman spectrum correction system and method |
| EP3546924A4 (en) * | 2016-11-22 | 2019-12-18 | Rion Co., Ltd. | Biological particle counting system and biological particle counting method |
| KR101847411B1 (en) | 2017-03-09 | 2018-04-10 | 서울대학교산학협력단 | Quantitative analysis system and method |
| CN109520983A (en) * | 2018-11-20 | 2019-03-26 | 山东船舶技术研究院 | A kind of quality evaluation method and device based on DOM |
| CN109520983B (en) * | 2018-11-20 | 2021-02-12 | 山东船舶技术研究院 | DOM-based water quality evaluation method and device |
| CN112268886A (en) * | 2020-09-04 | 2021-01-26 | 武汉光谷航天三江激光产业技术研究院有限公司 | Laser rapid detection and disinfection integrated device and method for virus and bacteria |
| KR20220111362A (en) * | 2021-02-02 | 2022-08-09 | (주)미디어에버 | Integrated system for identifying species of microbe in real-time |
| KR20220111360A (en) * | 2021-02-02 | 2022-08-09 | (주)미디어에버 | Apparatus for identifying species of microbe in real-time |
| KR102469053B1 (en) * | 2021-02-02 | 2022-11-22 | (주)미디어에버 | Apparatus for identifying species of microbe in real-time |
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