Atomic force microscopy as a tool for testing biomedical samples and elimination probe artifacts

Jedna od najperspektivnijih tehnika za ispitivanje sastava, strukture i svojstava materijala jeste mikroskopija sondama za skeniranje (SPM), odnosno njene komponente mikroskopija tunelovanjem elektrona (STM) i mikroskopija atomskim silama (AFM). Ovim metodama se rutinski postiže nanometarska i atomska rezolucija. Posebno istaknuta prednost metode je da ne postoje ograničenja u smislu porekla i sastava uzoraka, te je moguće ispitivanje organskih i neorganskih materijala. Ova tehnika se primenjuje u savremenim multidisciplinarnim istraživanjima u oblasti medicine, farmacije, stomatologije, nauke o materijalima, itd., i to za ispitivanje bioloških uzoraka, hemijskih jedinjenja, farmaceutskih proizvoda, veštačkih tkiva, materijala za implantologiju, i svih ostalih materijala čija nanotehnološka svojstva imaju uticaj na primenu u navedenim naučnim oblastima. Međutim, snimci dobijeni pomoću AFM-a samo su aproksimacije površina uzoraka, jer sonde nemaju ni savršenu veličinu ni geometriju, usled čega dolazi do pojave artefakata koji se definišu kao karakteristike koje se pojavljuju na snimku a koje nisu prisutne na ispitivanom uzorku. Ovi efekti izazvani konvolucijom između sonde i uzorka mogu do izvesne mere da budu korigovani matematičkom manipulacijom topografskim podacima. Metodologija koja je u ovom radu korišćena zasniva se na algebri skupova i osnovnim alatima matematičke morfologije. Iskorišćeni su matematički algoritmi za "slepu rekonstrukciju" vrhova sondi, a potom je izvršena dekonvolucija, da bi se otkrili delovi površine uzorka koji u realnosti nisu bili dostupni. Granica realnog vrha sonde izračunava se iz slike pomoću morfoloških ograničenja koja su inherentna u procesu snimanja. Rezultat se dobija u vidu snimka rekonstruisane površine uzorka iz dobijenih snimaka, uz pomoć rekonstrukcije vrha sonde kojom je uzorak sniman. Prikazani rezultati očigledan su dokaz upotrebne vrednosti mikroskopije atomskim silama kao tehnike za snimanja bioloških materijala u nanodimenzionalnom svetu, a primenjeni algoritmi povećavaju upotrebnu vrednost snimaka u smislu boljeg zaključivanja na osnovu preciznijih numeričkih podataka uzetih sa procesuiranih snimaka.One of the most perspective available techniques for investigation of the composition, structure and properties of materials, is scanning probe microscopy (SPM), respectively its components scanning tunneling microscopy (STM) and atomic force microscopy (AFM). This technique is used in multidisciplinary research in the field of medicine, pharmacy, dentistry, material science, etc., for study of biological samples, chemical compounds, pharmaceutical products, artificial tissues, implantology materials, and all other materials that have nanotechnological impact on application in these scientific fields. This is because the probes have not perfect size and geometry, which leads to the appearance of artifacts. They are defined as characteristics that appear on the image and are not present on the sample. These effects caused by convolutions between the probe and sample can be corrected to a certain extent by mathematical manipulation of topographic data. The methodology used in this paper is based on algebra of sets, and basic tools of mathematical morphology. Mathematical algorithms for the "blind reconstruction" of the tip were used, and then in order to detect the parts of the sample surface which is not available in real-time scanning deconvolution was applied. The limit of the real probe tip is calculated from the image, using the morphological limitations inherent in the recording process. The result acuired as an image of the reconstructed surface out of the used images, with the reconstruction of the real tip. The presented results are clear proof of the usability of atomic force microscopy as a technique for imaging of biological materials on nano-level, and the applied algorithms increase the usability of the images in terms of a better conclusion based on precise numerical data taken from the processed images

Atomic force microscopy as a tool for testing biomedical samples and elimination probe artifacts

Jedna od najperspektivnijih tehnika za ispitivanje sastava, strukture i svojstava materijala jeste mikroskopija sondama za skeniranje (SPM), odnosno njene komponente mikroskopija tunelovanjem elektrona (STM) i mikroskopija atomskim silama (AFM). Ovim metodama se rutinski postiže nanometarska i atomska rezolucija. Posebno istaknuta prednost metode je da ne postoje ograničenja u smislu porekla i sastava uzoraka, te je moguće ispitivanje organskih i neorganskih materijala. Ova tehnika se primenjuje u savremenim multidisciplinarnim istraživanjima u oblasti medicine, farmacije, stomatologije, nauke o materijalima, itd., i to za ispitivanje bioloških uzoraka, hemijskih jedinjenja, farmaceutskih proizvoda, veštačkih tkiva, materijala za implantologiju, i svih ostalih materijala čija nanotehnološka svojstva imaju uticaj na primenu u navedenim naučnim oblastima. Međutim, snimci dobijeni pomoću AFM-a samo su aproksimacije površina uzoraka, jer sonde nemaju ni savršenu veličinu ni geometriju, usled čega dolazi do pojave artefakata koji se definišu kao karakteristike koje se pojavljuju na snimku a koje nisu prisutne na ispitivanom uzorku. Ovi efekti izazvani konvolucijom između sonde i uzorka mogu do izvesne mere da budu korigovani matematičkom manipulacijom topografskim podacima. Metodologija koja je u ovom radu korišćena zasniva se na algebri skupova i osnovnim alatima matematičke morfologije. Iskorišćeni su matematički algoritmi za "slepu rekonstrukciju" vrhova sondi, a potom je izvršena dekonvolucija, da bi se otkrili delovi površine uzorka koji u realnosti nisu bili dostupni. Granica realnog vrha sonde izračunava se iz slike pomoću morfoloških ograničenja koja su inherentna u procesu snimanja. Rezultat se dobija u vidu snimka rekonstruisane površine uzorka iz dobijenih snimaka, uz pomoć rekonstrukcije vrha sonde kojom je uzorak sniman. Prikazani rezultati očigledan su dokaz upotrebne vrednosti mikroskopije atomskim silama kao tehnike za snimanja bioloških materijala u nanodimenzionalnom svetu, a primenjeni algoritmi povećavaju upotrebnu vrednost snimaka u smislu boljeg zaključivanja na osnovu preciznijih numeričkih podataka uzetih sa procesuiranih snimaka.One of the most perspective available techniques for investigation of the composition, structure and properties of materials, is scanning probe microscopy (SPM), respectively its components scanning tunneling microscopy (STM) and atomic force microscopy (AFM). This technique is used in multidisciplinary research in the field of medicine, pharmacy, dentistry, material science, etc., for study of biological samples, chemical compounds, pharmaceutical products, artificial tissues, implantology materials, and all other materials that have nanotechnological impact on application in these scientific fields. This is because the probes have not perfect size and geometry, which leads to the appearance of artifacts. They are defined as characteristics that appear on the image and are not present on the sample. These effects caused by convolutions between the probe and sample can be corrected to a certain extent by mathematical manipulation of topographic data. The methodology used in this paper is based on algebra of sets, and basic tools of mathematical morphology. Mathematical algorithms for the "blind reconstruction" of the tip were used, and then in order to detect the parts of the sample surface which is not available in real-time scanning deconvolution was applied. The limit of the real probe tip is calculated from the image, using the morphological limitations inherent in the recording process. The result acuired as an image of the reconstructed surface out of the used images, with the reconstruction of the real tip. The presented results are clear proof of the usability of atomic force microscopy as a technique for imaging of biological materials on nano-level, and the applied algorithms increase the usability of the images in terms of a better conclusion based on precise numerical data taken from the processed images

New approach to detection of abnormal cervical cells

Optomagnetna imidžing spektroskopija pokazala je visok procenat tačnosti u klasifikaciji bioloških tkiva, posebno kada se radi o uzorcima grlića materice, usne duplje i debelog creva. Ova metoda omogućava detekciju abnormalnog tkiva i ćelija i stoga može da se koristi kao dijagnostički test u okviru skrining programa. U prethodnim studijama analizirani su cervikalni uzorci i uzorci dobijeni tehnikom citologije na tečnoj bazi pomoću optomagnetne imidžing spektroskopije u cilju detekcije karcinoma grlića materice i pokazano je da ova metoda može da razdvoji zdravo tkivo od kancera. Do sada su testirani samo binarni klasifikacioni modeli za kasifikaciju cervikalnih uzoraka na bazi optomagnetnih spektara uzoraka. U ovom radu testirana je klasifikacija Papanikolaou razmaza u četiri klase (II, III, IV i V Papanikolaou grupe) korišćenjem klasifikacionog modela na bazi Random Forest klasifikatora koji je pokazao interklasnu senzitivnost od 49,25%, 58,97%, 50%, 44,44% za II, III, IV i V Papanikolau grupu respektivno, i specifičnost od 65,26%, 54,76%, 98,70% i 98,69% za II, III, IV i V Papanikolau grupu respektivno.Optomagnetic Imaging Spectroscopy demonstrated high percentages of accuracy in biological sample classification, namely cervical, oral and colon samples. It enables detection of abnormal tissue and cells, and thus can be used as a diagnostic tool in screening programs. Papanicolaou smears and liquid based cytology samples were analysed in previous studies on cervical cancer detection by Optomagnetic Imaging Spectroscopy and it was shown that this method can diferentiate normal healthy tissue from the cancer tissue. So far, only binary classification of the cervical samples was performed based on optomagnetic spectra of the samples. In this paper, classification of the Papanicolaou smears into four groups (II, III, IV and V Papanicolaou groups) was tested with the Random Forest classification model that demonstrated interclass sensitivity of 49.25%, 58.97%, 50%, 44.44% for II, III, IV and V Papanicolaou group respectively, and specificity of 65.26%, 54.76%, 98.70% and 98.69% for II, III, IV and V Papanicolaou group respectively

New approach to detection of abnormal cervical cells

Optomagnetna imidžing spektroskopija pokazala je visok procenat tačnosti u klasifikaciji bioloških tkiva, posebno kada se radi o uzorcima grlića materice, usne duplje i debelog creva. Ova metoda omogućava detekciju abnormalnog tkiva i ćelija i stoga može da se koristi kao dijagnostički test u okviru skrining programa. U prethodnim studijama analizirani su cervikalni uzorci i uzorci dobijeni tehnikom citologije na tečnoj bazi pomoću optomagnetne imidžing spektroskopije u cilju detekcije karcinoma grlića materice i pokazano je da ova metoda može da razdvoji zdravo tkivo od kancera. Do sada su testirani samo binarni klasifikacioni modeli za kasifikaciju cervikalnih uzoraka na bazi optomagnetnih spektara uzoraka. U ovom radu testirana je klasifikacija Papanikolaou razmaza u četiri klase (II, III, IV i V Papanikolaou grupe) korišćenjem klasifikacionog modela na bazi Random Forest klasifikatora koji je pokazao interklasnu senzitivnost od 49,25%, 58,97%, 50%, 44,44% za II, III, IV i V Papanikolau grupu respektivno, i specifičnost od 65,26%, 54,76%, 98,70% i 98,69% za II, III, IV i V Papanikolau grupu respektivno.Optomagnetic Imaging Spectroscopy demonstrated high percentages of accuracy in biological sample classification, namely cervical, oral and colon samples. It enables detection of abnormal tissue and cells, and thus can be used as a diagnostic tool in screening programs. Papanicolaou smears and liquid based cytology samples were analysed in previous studies on cervical cancer detection by Optomagnetic Imaging Spectroscopy and it was shown that this method can diferentiate normal healthy tissue from the cancer tissue. So far, only binary classification of the cervical samples was performed based on optomagnetic spectra of the samples. In this paper, classification of the Papanicolaou smears into four groups (II, III, IV and V Papanicolaou groups) was tested with the Random Forest classification model that demonstrated interclass sensitivity of 49.25%, 58.97%, 50%, 44.44% for II, III, IV and V Papanicolaou group respectively, and specificity of 65.26%, 54.76%, 98.70% and 98.69% for II, III, IV and V Papanicolaou group respectively

Opto-Magnetic Method for Epstein - Barr Virus and Cytomegalovirus Detection in Blood Plasma Samples

Motivated by characterization of paramagnetic materials (Al, Mn and Ti) and diamagnetic materials (Cu, C and Zn) by opto-magnetic method that is based on light-matter interaction using digital imaging, we present results of Epstein Barr virus (EBV) and cytomegalovirus (CMV) detection in blood plasma. To investigate light-blood plasma interaction we use wavelength difference of diffuse white light and reflected polarized light in red and blue channels of digital images (opto-magnetic method). Digital images of samples are analyzed by spectral convolution algorithm for light-matter interaction analysis. Since opto-magnetic method can detect very small difference between normal and pathological tissue states it is advantageous in comparison with classical methods. Especially it is important for early detection of suspicious tissue states and detection of viral infection presence in plasma. We compared our results with results of standard biomedical test for EBV and CVM, as a reference, and found out for group of 40 samples significant correlation of 93. 6%

Papanicolaou stained cervical smear analysis using opto-magnetic imaging spectroscopy

Karcinom grlića materice je drugi po redu najčešći oblik invazivnog karcinoma kod žena. U ovoj studiji, uzorci pripremljeni za standardni Pap test su ispitivani imidžing softverom koji analizira razliku između reflektovane difuzne bele svetlosti i reflektovane polarizovane svetlosti (opto-magnetna imidžing spektroskopija) u cilju detektovanja normalnih ćelija, displactičnih ćelija i ćelija kancepa. Digitalna kamepa prilagođena za prikupljanje OMIC slika uzoraka i softvep za analizu opto-magnetnih slika omogućili su dobijanje finijeg razdvajanja normalnih nalaza od onih koji sadrže displastične ćelije ili ćelije kancera. S obzirom da ova metoda detektuje značajne razlike između standardnih Pap kategorija, pokazana je njena prednost u odnosu na konvencionalne metode za ranu detekciju kancera. Opto-magnetna imidžing spektroskopija daje rezultate koji nisu zavisni od stručnosti, subjektivnosti i iskustva praktičara.Cervical cancer is the second most common invasive cancer of the female genital tract. In this study, samples prepared for standard Pap test were used and examined using digital imaging software that analyzes the difference between reflected diffuse white light and reflected polarized light (opto-magnetic imaging spectrosopy) in order to detect normal, dysplastic and cancerous cells. A digital camera customized for taking OMIS pictures of samples and light-mater interaction software for opto-magnetic image analysis guided the diagnostic decision to more refined distinction between normal smear and the one containing either dysplastic or cancerous cells. Since the application of OMIS enables detection of significant differences between standard Pap test categories, this method offers an advantage over classical methods in the area of early detection of suspicious cells. By this method it is possible to obtain the result that is not dependent on the capability, subjectivity, experience and knowledge of the practitioner

Papanicolaou stained cervical smear analysis using opto-magnetic imaging spectroscopy

Karcinom grlića materice je drugi po redu najčešći oblik invazivnog karcinoma kod žena. U ovoj studiji, uzorci pripremljeni za standardni Pap test su ispitivani imidžing softverom koji analizira razliku između reflektovane difuzne bele svetlosti i reflektovane polarizovane svetlosti (opto-magnetna imidžing spektroskopija) u cilju detektovanja normalnih ćelija, displactičnih ćelija i ćelija kancepa. Digitalna kamepa prilagođena za prikupljanje OMIC slika uzoraka i softvep za analizu opto-magnetnih slika omogućili su dobijanje finijeg razdvajanja normalnih nalaza od onih koji sadrže displastične ćelije ili ćelije kancera. S obzirom da ova metoda detektuje značajne razlike između standardnih Pap kategorija, pokazana je njena prednost u odnosu na konvencionalne metode za ranu detekciju kancera. Opto-magnetna imidžing spektroskopija daje rezultate koji nisu zavisni od stručnosti, subjektivnosti i iskustva praktičara.Cervical cancer is the second most common invasive cancer of the female genital tract. In this study, samples prepared for standard Pap test were used and examined using digital imaging software that analyzes the difference between reflected diffuse white light and reflected polarized light (opto-magnetic imaging spectrosopy) in order to detect normal, dysplastic and cancerous cells. A digital camera customized for taking OMIS pictures of samples and light-mater interaction software for opto-magnetic image analysis guided the diagnostic decision to more refined distinction between normal smear and the one containing either dysplastic or cancerous cells. Since the application of OMIS enables detection of significant differences between standard Pap test categories, this method offers an advantage over classical methods in the area of early detection of suspicious cells. By this method it is possible to obtain the result that is not dependent on the capability, subjectivity, experience and knowledge of the practitioner

Classification of breast cancer luminescence data using self-organizing mapping neural network

Primenjena je samoorganizujuća neuronska mreža pri analizi podataka luminescencije raka dojke. Ulazni podaci su trodimenzionalni vektori koji predstavljaju normalno i maligno humano tkivo. Analizirana je mogućnost klasifikacije podataka u dve grupe. Mreža je zadovoljavajuće obavila klasifikaciju ulaznih podataka.Self-organizing mapping neural networks are applied in the analysis of breast cancer luminescence data. Data consist of three dimensional vectors presenting normal and malignant human tissue. The possibility of such data classification in two groups (normal and malignant tissue) is analyzed. The network performed successful classification

Classification of breast cancer luminescence data using self-organizing mapping neural network

Primenjena je samoorganizujuća neuronska mreža pri analizi podataka luminescencije raka dojke. Ulazni podaci su trodimenzionalni vektori koji predstavljaju normalno i maligno humano tkivo. Analizirana je mogućnost klasifikacije podataka u dve grupe. Mreža je zadovoljavajuće obavila klasifikaciju ulaznih podataka.Self-organizing mapping neural networks are applied in the analysis of breast cancer luminescence data. Data consist of three dimensional vectors presenting normal and malignant human tissue. The possibility of such data classification in two groups (normal and malignant tissue) is analyzed. The network performed successful classification

Possible approaches to LCA methodology for nanomaterials in sustainable energy production

Nanomaterijali imaju sve veću ulogu u brzo rastućoj oblasti održive proizvodnje energije. Pored dokazanih prednosti korišćenja nanomaterijala za inovacije u ovom domenu, njihov uticaj na životnu sredinu i zdravlje ljudi je još uvek nedovoljno ispitan. S tim u vezi, nalaženje odgovarajućih metoda za analizu, procjenu i tretman potencijalnih efekata primjene nanotehnologije na životnu sredinu i zdravlje ljudi je više nego neophodno. U ovom radu pokušaćemo da predstavimo kratak pregled moguće primjene procjene životnog ciklusa (LCA) na nanometerijale korišćene u određenim aplikcijama za održivu proizvodnju energije. Korišćenje ove metode bi takođe trebalo da pruži mogućnost za poređenje novih tehnologija sa već postojećim konvencionalnim tehnologijama u smislu njihovih uticaja na životnu sredinu, zdravlje i bezbjednost.Nano-engineered materials are playing an ever growing role in the rapidly developing field of sustainable energy production. Besides providing numerous opportunities for innovations in this domain, utilisation of nanostructured materials raises numerous doubts regarding their impact on the environment and possible adverse effects on human health. Providing reliable methods for analysis, evaluation and dealing with the environmental and health effects of nanotechnology is therefore crucial. In this article we will try to give an outline of possible approaches to deployment of Life Cycle Assessment (LCA) tools to nanomaterials used in certain applications for sustainable energy production. Use of such methods should also provide the possibility of comparing these new, emerging, technologies with that of already existing conventional ones in terms of their environmental, health and safety impacts