Diagnostics Of Various Diseases Research Articles

Impact of breath sample collection method and length of storage of breath samples in Tedlar bags on the level of selected volatiles assessed using gas chromatography-ion mobility spectrometry (GC-IMS)

The analysis of volatile organic compounds (VOCs) in exhaled air has attracted the interest of the scientific community because it provides the possibility of monitoring physiological and metabolic processes and non-invasive diagnostics of various diseases. However, this method remains underused in clinical practice as well as in research because of the lack of standardized procedures for the collection, storage and transport of breath samples, which would guarantee good reproducibility and comparability of results. The method of sampling, as well as the storage time of the breath samples in the polymer bags used for sample storage and transport, affect the composition and concentration of VOCs present in the breath samples. The aim of our study was to compare breath samples obtained using two methods with fully disposable equipment: a Haldane sampling tube intended for direct breath collection and breath samples exhaled into a transparent Tedlar bag. The second task was to monitor the stability of selected compounds of real breath samples stored in a Tedlar bag for 6 h. Gas chromatography coupled with ion mobility spectrometry (GC-IMS) implemented in the BreathSpec® device was used to analyse exhaled breath. Our results showed a significant difference in the signal intensity of some volatiles when taking a breath sample with a Haldane tube and a Tedlar bag. Due to its endogenous origin, acetone levels were significantly higher when the Haldane tube sampler was used while elevated levels of 2-propanol and unidentified VOC (designated as VOC 3) in the Tedlar bag samples likely originated from contamination of the Tedlar bags. The VOC stability study revealed compound-specific signal intensity changes of the selected VOCs with storage time in the Tedlar bags, with some volatiles showing increasing signal intensity during storage in Tedlar bags. This limits the use of Tedlar bags only for very limited time and carefully selected purpose. Our results highlight the importance of careful design and implementation of experiments and clinical protocols to obtain relevant and reliable results.

Quantum Dot-Antibody Conjugates for Immunofluorescence Studies of Biomolecules and Subcellular Structures.

Quantum dots, or nanoscale semiconductors, are one of the most important materials for various research and development purposes. Due to their advantageous photoluminescence and electronic properties, namely, their unique photostability, high brightness, narrow emission spectra from visible to near-infrared wavelengths, convey them significant advantages over widely used fluorochromes, including organic dyes, fluorescent probes. Quantum dots are a unique instrument for a wide range of immunoassays with antibodies. The paper provides an overview of the developed and already applied methods of quantum dot surface modification, quantum dots conjugation to different antibodies (non-covalent, direct covalent linkage or with the use of special adapter molecules), as well as practical examples of recent quantum dot-antibody applications in the immunofluorescence microscopy for cell and cell structure imaging, fluorescent assays for biomolecules detection and in diagnostics of various diseases. The review presents advantages of quantum dot-antibody conjugation technology over the existing methods of immunofluorescence studies and a forward look into its potential prospects in biological and biomedical research.

Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning.

Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.

Diagnostic value of microbiome biomarkers of the periodonite microbiome in patients with the association of chronic periodontitis and diabetes mellitus type 2.

The place of high-tech methods of molecular biology in clinical laboratory diagnostics of various diseases and the development of a system of biomarkers as an important component of diagnostic research is currently attracting the closest attention of the scientific community. In this paper, an attempt is made to use high-tech metagenomic analysis to solve problems that arise due to the high frequency of association of periodontal diseases with systemic pathology, in particular, with type 2 diabetes mellitus. The aim of the study was to determine the taxonomic and metabolic features of the microbiome of periodontal tissues in periodontal diseases associated with type 2 diabetes mellitus, as a model of the ratio of local and systemic effects of periodontal pathogenic bacteria. The study included 16S shotgun sequencing of bacterial DNA as part of biological material from periodontal pockets/dentoalveolar furrows of 46 people - 15 patients with chronic periodontitis associated with type 2 diabetes mellitus, 15 patients with chronic periodontitis unrelated to systemic pathology, as well as 16 healthy people in the control group, followed by bioinformatic processing of the data obtained. The obtained data allowed us to establish the taxonomic features of the periodontal microbiome in the association of chronic periodontitis with type 2 diabetes mellitus, which included the predominance of representatives of the families Prevotellaceae and Spirochaetaceae in its composition. The features of metabolic processes in periodontal tissues with the participation of the microbiome were also revealed, which consisted in an increase in the exchange of cysteine and methionine against the background of a decrease in the metabolism of pyrimidine, methane, sphingolipids, and the synthesis of fatty acids, which are of diagnostic value in assessing the condition of patients with type 2 diabetes mellitus.

Digital Natives' Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study.

BackgroundArtificial intelligence (AI) has shown potential to improve diagnostics of various diseases, especially for early detection of skin cancer. Studies have yet to investigate the clear application of AI technology in clinical practice or determine the added value for younger user groups. Translation of AI-based diagnostic tools can only be successful if they are accepted by potential users. Young adults as digital natives may offer the greatest potential for successful implementation of AI into clinical practice, while at the same time, representing the future generation of skin cancer screening participants.ObjectiveWe conducted an anonymous online survey to examine how and to what extent individuals are willing to accept AI-based mobile apps for skin cancer diagnostics. We evaluated preferences and relative influences of concerns, with a focus on younger age groups.MethodsWe recruited participants below 35 years of age using three social media channels—Facebook, LinkedIn, and Xing. Descriptive analysis and statistical tests were performed to evaluate participants’ attitudes toward mobile apps for skin examination. We integrated an adaptive choice-based conjoint to assess participants’ preferences. We evaluated potential concerns using maximum difference scaling.ResultsWe included 728 participants in the analysis. The majority of participants (66.5%, 484/728; 95% CI 0.631-0.699) expressed a positive attitude toward the use of AI-based apps. In particular, participants residing in big cities or small towns (P=.02) and individuals that were familiar with the use of health or fitness apps (P=.02) were significantly more open to mobile diagnostic systems. Hierarchical Bayes estimation of the preferences of participants with a positive attitude (n=484) revealed that the use of mobile apps as an assistance system was preferred. Participants ruled out app versions with an accuracy of ≤65%, apps using data storage without encryption, and systems that did not provide background information about the decision-making process. However, participants did not mind their data being used anonymously for research purposes, nor did they object to the inclusion of clinical patient information in the decision-making process. Maximum difference scaling analysis for the negative-minded participant group (n=244) showed that data security, insufficient trust in the app, and lack of personal interaction represented the dominant concerns with respect to app use.ConclusionsThe majority of potential future users below 35 years of age were ready to accept AI-based diagnostic solutions for early detection of skin cancer. However, for translation into clinical practice, the participants’ demands for increased transparency and explainability of AI-based tools seem to be critical. Altogether, digital natives between 18 and 24 years and between 25 and 34 years of age expressed similar preferences and concerns when compared both to each other and to results obtained by previous studies that included other age groups.

Sensor activity of titanium dioxide nanotubes in relation to acetone molecules

This paper presents the theoretical study results of the possibility of acetone, common volatile organic compound (VOCs) in human respiration, with titanium dioxide nanotubes. The efficiency of interaction of the acetone molecule with the TiO2 nanotube is analyzed. Recommendations for the creation of highly sensitive sensor devices using titanium dioxide nanotubes for diagnostics of various diseases have been developed.

Investigation of Surface-Functionalized CNT-Based Array for Detection of Acetone Vapors

This article provides a theoretical study of the possibility of reacting acetone, a common volatile organic compound (VOC) in human respiration, with carbon nanotubes modified with functional groups - carboxyl and amine. Analysis of efficiency of processes of sorption interaction of acetone molecule with modified nanosystem for development of recommendations for creation of perspective highly sensitive sensory devices using modified carbon nanotubes for detection of VOCs contained in human exhalation and diagnostics of various diseases.

Online breath analysis using metal oxide semiconductor sensors (electronic nose) for diagnosis of lung cancer

The analysis of exhaled breath is drawing a high degree of interest in the diagnostics of various diseases, including lung cancer. Electronic nose (E-nose) technology is one of the perspective approaches in the field due to its relative simplicity and cost efficiency. The use of an E-nose together with pattern recognition algorithms allow ‘breath-prints’ to be discriminated. The aim of this study was to develop an efficient online E-nose-based lung cancer diagnostic method via exhaled breath analysis with the use of some statistical classification methods. A developed multisensory system consisting of six metal oxide chemoresistance gas sensors was employed in three temperature regimes. This study involved 118 individuals: 65 in the lung cancer group (cytologically verified) and 53 in the healthy control group. The exhaled breath samples of the volunteers were analysed using the developed E-nose system. The dataset obtained, consisting of the sensor responses, was pre-processed and split into training (70%) and test (30%) subsets. The training data was used to fit the classification models; the test data was used for the estimation of prediction possibility. Logistic regression was found to be an adequate data-processing approach. The performance of the developed method was promising for the screening purposes (sensitivity—95.0%, specificity—100.0%, accuracy—97.2%). This shows the applicability of the gas-sensitive sensor array for the exhaled breath diagnostics. Metal oxide sensors are highly sensitive, low-cost and stable, and their poor sensitivity can be enhanced by integrating them with machine learning algorithms, as can be seen in this study. All experiments were carried out with the permission of the N.N. Petrov Research Institute of Oncology ethics committee no. 15/83 dated March 15, 2017.

Biomarkers and Spectroscopic Methods: The Strategies for Diagnostics of Selected Diseases

Background: There are many different tools for diagnostics of various diseases. One of the simplest approach for the early, rapid and accurate diagnosis represents determination of biomarkers. </P><P> Focus: In the following text, we describe review of the latest discoveries in the field of biomarkers of selected diseases: intestinal ischemia and atherosclerosis. The aim of this review article is to show the problems which the researchers have been dealing with in the process of discovering and establishing novel biomarkers. This work describes the possibilities of monitoring biomarkers from noninvasive samples such as tears. Additionally, the actual possibilities of the spectroscopy techniques in monitoring and diagnostics of selected diseases are mentioned which might replace the need of biomarkers of several diseases. </P><P> Prospect: For the most diagnostic purposes, biomarkers should be analyzed in body fluid samples. For the biofluids, metabolic signatures could be determined, although there is no consensus on possible biomarkers yet. Metabolomics, the comprehensive, qualitative, and quantitative study of secondary metabolites and signaling molecules reveal a wide range of dysregulated molecules in various diseases. However, using spectroscopic methods could contribute to the traditional view on biomarkers by monitoring the relevant tissues and body fluid samples.

The Use of IR Fourier Spectroscopy of Saliva for Rapid Assessment of the Level of Lipid Peroxidation Products

Infrared spectroscopy of saliva is an express and non-invasive method of analysis, applicable for diagnostics of various diseases and for studying metabolic processes and adaptive changes in the body. The goal of this study was to determine possibility of analyzing the products of lipid peroxidation (LPO) by using IR spectroscopy of saliva on the example of oncological diseases. The study involved 203 patients with lung cancer (n = 40), breast cancer (n = 50) and the control group (n = 113). Saliva samples were collected in the morning after overnight fast. The content of LPO products (conjugated dienes, and trienes, Schiff bases, malonic dialdehyde MDA) was determined in all samples and the IR absorption spectra were recorded in the range of 500–4000 cm–1. In the IR spectra, an increase in the intensity of the absorption bands of lipids was observed; it corresponded to an increase in the total lipid content and correlated with the content of MDA, and a decrease in the intensity of vibrations of oxygen-containing groups, which corresponded to a negative correlation with secondary LPO products. Apparently, on the IR spectra, we simultaneously register both primary, intermediate, and final LPO products. Statistically significant regression equations were obtained, allowing to estimate the content of intermediate LPO products - conjugated triene, and Schiff bases. The proposed method allows to monitor LPO processes, as well as to characterize the direction of the equilibrium shift in these processes.

A review on the role of lipid-based nanoparticles in medical diagnosis and imaging.

Molecular and diagnostic imaging has been recently a subject of intense research in the treatment of numerous diseases. In medical imaging, there are different modalities with unique strengths including MRI, ultrasound imaging, computed tomography, positron emission tomography and single photon emission computed tomography. These systems need specific contrast agents to achieve a suitable image with the best quality. Nanoparticles represent an innovative tool in imaging field research and diagnostics of various diseases, especially cancerous ones. Among the nanocarriers, lipid-based nanoparticles, such as nanostructured lipid carriers, solid lipid nanoparticles and liposomes, are the most used carriers in imaging because of having many advantageous properties. This review addresses advancements in different lipid-based nanoparticles as tools in medical diagnostic and imaging.

Evaluation of Timepix3 based CdTe photon counting detector for fully spectroscopic small animal SPECT imaging

The imaging method of SPECT (Single Photon Emission Computed Tomography) is used in nuclear medicine for diagnostics of various diseases or organs malfunctions. The distribution of medically injected, inhaled, or ingested radionuclides (radiotracers) in the patient body is imaged using gamma-ray sensitive camera with suitable imaging collimator. The 3D image is then calculated by combining many images taken from different observation angles. Most of SPECT systems use scintillator based cameras. These cameras do not provide good energy resolution and do not allow efficient suppression of unwanted signals such as those caused by Compton scattering. The main goal of this work is evaluation of Timepix3 detector properties for SPECT method for functional imaging of small animals during preclinical studies. Advantageous Timepix3 properties such as energy and spatial resolution are exploited for significant image quality improvement. Preliminary measurements were performed on specially prepared plastic phantom with cavities filled by radioisotopes and then repeated with in vivo mouse sample.

Study of properties and development of sensors based on graphene films grown on SiC (0001) by thermal destruction method

The structural, chemical, and electronic properties of epitaxial graphene films grown by thermal decomposition of the Si-face of a semi-insulating 6H-SiC substrate in an argon environment are studied by Raman spectroscopy, X-ray photoelectron spectroscopy and angle-resolved photoemission. It was demonstrated the possibility of fabrication of the gas and biosensors that is based on grown graphene films. The gas sensors are sufficiently sensitive to NO2 at low concentrations. The biosensor operation was checked using an immunochemical system comprising fluorescein dye and monoclonal anti fluorescein antibodies. The sensor detects fluorescein concentration on a level of 1–10 ng/mL and bovine serum albumin– fluorescein conjugate on a level of 1–5 ng/mL. The proposed device has good prospects for use for early diagnostics of various diseases.

Label-free chronopotentiometric glycoprofiling of prostate specific antigen using sialic acid recognizing lectins

In recent decades, it has become clear that most of human proteins are glycosylated and that protein glycosylation plays an important role in health and diseases. At present, simple, fast and inexpensive methods are sought for clinical applications and particularly for improved diagnostics of various diseases, including cancer. We propose a label- and reagent-free electrochemical method based on chronopotentiometric stripping (CPS) analysis and a hanging mercury drop electrode for the detection of interaction of sialylated protein biomarker a prostate specific antigen (PSA) with two important lectins: Sambucus nigra agglutinin (SNA) and Maackia amurensis agglutinin (MAA). Incubation of PSA-modified electrode with specific SNA lectin resulted in an increase of CPS peak H of the complex as compared to this peak of individual PSA. By adjusting polarization current and temperature, PSA-MAA interaction can be either eliminated or distinguished from the more abundant PSA-SNA complex. CPS data were in a good agreement with the data obtained by complementary methods, namely surface plasmon resonance and fluorescent lectin microarray. It can be anticipated that CPS will find application in glycomics and proteomics.

An improved arteriovenous classification method for the early diagnostics of various diseases in retinal image

(Background and objectives)Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. (Methods)Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins. (Results)The proposed method was tested on the DRIVE dataset and achieved an overall accuracy of 0.923. (Conclusion)This retinal artery and vein classification algorithm serves as a potentially important tool for the early diagnosis of various diseases, including diabetic retinopathy and cardiovascular diseases.

APPLICATION IMMUNOHISTOCHEMICALLY RESEARCH METHODS IN THE DIAGNOSIS OF PROSTATE CANCER

Introduction. The actual problem of modern urology remains differential diagnostics of various diseases of the prostate gland. The purpose of the study. Increasing the effectiveness of differential diagnosis of diseases of the prostate. Materials and methods. In the biopsy specimens of patients with benign prostatic hyperplasia (BPH) and prostate cancer (PCa), an immunohistochemical study of the production of the Ki-67 proliferation marker, matrix metalloproteinase-9, the matrix metalloproteinase inhibitor TIMP-1, and the distribution of collagen type IV was performed. Results. A moderate positive correlation was found between Gleason gradation and the cell proliferation index for Ki 67 (rs = 0.674) and a moderate negative correlation of Gleason gradation with the level of production of matrix metalloproteinase-9 (rs = -0.660). A weak significant negative correlation was established between the level of proliferative cell activity and the production of MMP-9 tumor cells (rs = -0.369). A significant decrease in the level of MMP-9 and TIMP-1 in adenocarcinoma of different grades was revealed. The invasive properties of tumor cells, expressed in the destruction of collagen of the IV type of the basal membrane and connective tissue prostatic stroma, are mediated by the imbalance between MMP-9 and the protein blocking this enzyme - TIMP-1, whose production decreases in adenocarcinomas of different grades compared with BPH. Conclusions: 1. BPH is characterized by high production of MMP-9 type, which destroys the collagen of the basal membranes and stroma, the proteolytic action of which is blocked by the high content of TIMP-1.

Structure and individual anatomical variability of the I-III lobules of the human cerebellar hemispheres.

Background. Morphological changes of cerebellar lobules are found in many congenital and acquired diseases of the cerebellum. In recent years, thanks to modern imaging techniques morphological changes of the hemispheric and vermal lobules can be detected in vivo. However, criteria of imaging diagnostic methods which are based on information about normal structure of the cerebellum, do not take into account the features of individual anatomical variability, gender and age characteristics. Objective - to investigate individual variability and features of variant anatomy of the I-III lobules of the human cerebellar hemispheres. Methods. Research was conducted at the Kharkiv regional bureau of forensic medicine on 100 cerebellums of people of both sexes 20-99 years old who died of causes unrelated to brain pathology. During the forensic autopsy the cerebellum and brain stem were separated and fixed during one month in 10% formalin solution. Parasagittal sections of cerebellar hemispheres were investigated. Results. The shape of the I-III lobules of the human cerebellar hemispheres is quite varied. Differences of the structure of these lobules depend on the characteristics of the branching of the white matter, the number of secondary branches and cerebellar folia. We described 4 variants of the shape of the II-III lobules of the human cerebellar hemispheres; 3rd variant is the most common. That variant can be used as anatomical standard of the lobules. Conclusion. Described variants of the shape of the cerebellar lobules can be used as criteria standards in current imaging techniques for the diagnostics of various diseases of the CNS.

Graphene-based biosensors

Results of developing and testing graphene-based sensors capable of detecting protein molecules are presented. The biosensor operation was checked using an immunochemical system comprising fluorescein dye and monoclonal antifluorescein antibodies. The sensor detects fluorescein concentration on a level of 1–10 ng/mL and bovine serum albumin–fluorescein conjugate on a level of 1–5 ng/mL. The proposed device has good prospects for use for early diagnostics of various diseases.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey.

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

Immunosensors in Clinical Laboratory Diagnostics.

The application of simple, cost-effective, rapid, and accurate diagnostic technologies for detection and identification of cardiac and cancer biomarkers has been a central point in the clinical area. Biosensors have been recognized as efficient alternatives for the diagnostics of various diseases due to their specificity and potential for application on real samples. The role of nanotechnology in the construction of immunological biosensors, that is, immunosensors, has contributed to the improvement of sensitivity, since they are based in the affinity between antibody and antigen. Other analytes than biomarkers such as hormones, pathogenic bacteria, and virus have also been detected by immunosensors for clinical point-of-care applications. In this chapter, we first introduced the various types of immunosensors and discussed their applications in clinical diagnostics over the recent 6 years, mainly as point-of-care technologies for the determination of cardiac and cancer biomarkers, hormones, pathogenic bacteria, and virus. The future perspectives of these devices in the field of clinical diagnostics are also evaluated.