Hybrid Impedimetric Biosensors for Express Protein Markers Detection.

Impedimetric biosensors represent a powerful and promising tool for studying and monitoring biological processes associated with proteins and can contribute to the development of new approaches in the diagnosis and treatment of diseases. The basic principles, analytical methods, and applications of hybrid impedimetric biosensors for express protein detection in biological fluids are described. The advantages of this type of biosensors, such as simplicity and speed of operation, sensitivity and selectivity of analysis, cost-effectiveness, and an ability to be integrated into hybrid microfluidic systems, are demonstrated. Current challenges and development prospects in this area are analyzed. They include (a) the selection of materials for electrodes and formation of nanostructures on their surface; (b) the development of efficient methods for biorecognition elements' deposition on the electrodes' surface, providing the specificity and sensitivity of biosensing; (c) the reducing of nonspecific binding and interference, which could affect specificity; (d) adapting biosensors to real samples and conditions of operation; (e) expanding the range of detected proteins; and, finally, (f) the development of biosensor integration into large microanalytical system technologies. This review could be useful for researchers working in the field of impedimetric biosensors for protein detection, as well as for those interested in the application of this type of biosensor in biomedical diagnostics.

Microstructural segmentation using a union of attention guided U-Net models with different color transformed images.

Metallographic images or often called the microstructures contain important information about metals, such as strength, toughness, ductility, corrosion resistance, which are used to choose the proper materials for various engineering applications. Thus by understanding the microstructures, one can determine the behaviour of a component made of a particular metal, and can predict the failure of that component in certain conditions. Image segmentation is a powerful technique for determination of morphological features of the microstructure like volume fraction, inclusion morphology, void, and crystal orientations. These are some key factors for determining the physical properties of metal. Therefore, automatic micro-structure characterization using image processing is useful for industrial applications which currently adopts deep learning-based segmentation models. In this paper, we propose a metallographic image segmentation method using an ensemble of modified U-Nets. Three U-Net models having the same architecture are separately fed with color transformed imaged (RGB, HSV and YUV). We improvise the U-Net with dilated convolutions and attention mechanisms to get finer grained features. Then we apply the sum-rule-based ensemble method on the outcomes of U-Net models to get the final prediction mask. We achieve the mean intersection over union (IoU) score of 0.677 on a publicly available standard dataset, namely MetalDAM. We also show that the proposed method obtains results comparable to state-of-the-art methods with fewer number of model parameters. The source code of the proposed work can be found at  https://github.com/mb16biswas/attention-unet .

Study of Laser Light Scattering Methods in Rapid Viability Assessment of Microorganisms under Antibiotics Exposure for Adaptation in Lab-on-A-Chip Format.

The antibiotic resistance (ABR) problem is becoming increasingly disturbing and it is important to implement express methods of ABR testing to allow operative antibiotic therapy decisions. The application of laser light scattering (LLS) in microbiological analysis for express ABR testing of microorganisms has been considered. The ways of miniaturization of laser light scattering for creating the bases of their integration into microbiological laboratory-on-a-chip (MLOC) for clinical express diagnostics have been analysed. The advantage of miniaturization in the context of clinical express analysis realization problems are investigated. A system of parallel measuring cells and illumination, enabling simultaneous testing of a group of antibiotics, was tested by splitting a laser beam with a two-dimensional collimator prepared of nanoporous anodic aluminum oxide. It has been demonstrated that the application of LLS methods, providing high concentration and mass sensitivity as well as a miniaturization potential, is an effective approach in the development of new generation diagnostic instruments. The studies have demonstrated the ability of methods to register effects of antibiotics on microbiological samples within 10 min. The following microorganisms were used in the study: Escherichia coli M-17, Lactobacillus plantarum, Bifidobacterium bifidum, Stenotrophomonas maltophilia.

Brain tumor image generation using an aggregation of GAN models with style transfer.

In the recent past, deep learning-based models have achieved tremendous success in computer vision-related tasks with the help of large-scale annotated datasets. An interesting application of deep learning is synthetic data generation, especially in the domain of medical image analysis. The need for such a task arises due to the scarcity of original data. Class imbalance is another reason for applying data augmentation techniques. Generative Adversarial Networks (GANs) are beneficial for synthetic image generation in various fields. However, stand-alone GANs may only fetch the localized features in the latent representation of an image, whereas combining different GANs might understand the distributed features. To this end, we have proposed AGGrGAN, an aggregation of three base GAN models-two variants of Deep Convolutional Generative Adversarial Network (DCGAN) and a Wasserstein GAN (WGAN) to generate synthetic MRI scans of brain tumors. Further, we have applied the style transfer technique to enhance the image resemblance. Our proposed model efficiently overcomes the limitation of data unavailability and can understand the information variance in multiple representations of the raw images. We have conducted all the experiments on the two publicly available datasets - the brain tumor dataset and the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2020 dataset. Results show that the proposed model can generate fine-quality images with maximum Structural Similarity Index Measure (SSIM) scores of 0.57 and 0.83 on the said two datasets.

Isolated Sphenoid Sinusitis: Anatomical Features for Choosing a Method of Treatment, a Case-Control Study.

Isolated sphenoid sinusitis (ISS) is a group of pathologies characterized by inflammation in one or both sphenoid sinuses. The gold standard for analyzing and diagnosing ISS is computer tomography. Many researchers have discussed the treatment of patients with ISS variants such as fully opacified sinus, mostly with surgery. A retrospective analysis of clinical data of 59 patients (21 male (35%), 38 female (65%)) with ISS, who were treated in the Otorhinolaryngological Department of Pavlov First Saint Petersburg State Medical University between January 2017 and January 2020, was conducted. All patients were in the first stage of the same medical therapy. In cases where there was no recovery, these patients were referred to surgery. For the control group, we analyzed patients without any disorders according to CT-scan examination. After analyzing the obtained clinical and radiological data, we found indicators that were common in patients who did not recover after medical therapy. According to the reverse regression method statistical model, in male patients with a diffuse headache and nasal discharge it was shown that medical therapy was highly effective (more than 78%). The presence of nasal septum deviation and adenoids in male and female patients leads to the highest risk of surgical treatment (83% probability of the logistic model). The detailed analysis of CT-scans and the complaints of patients with ISS can be the key to determining the preferred therapy choice. Not all cases need to have an endoscopic opening of the sphenoid sinus, according to our research.

Case Report: Oncocytic Schneiderian Papilloma Originating From the Sphenoid Sinus.

A rare case of oncocytic Schneiderian papilloma originating from the sphenoid sinus characterised, for 3 years, by non-specific symptoms of severe headache, a block of nasal breathing, and deprecating sense of smell was presented by an elderly female patient. Sphenoid sinus functional endoscopic sinus surgery (FESS), with a one-block tumour excision, through an endonasal approach, with a histological study of removed tumour masses, were performed on the patient. Long observation in the post-operative period was necessary, considering the risk of recurrence and malignancy of oncocytic Schneiderian papilloma (OSP). Although the oncocytic papilloma of the sphenoid sinus is rare, non-specific symptoms make this pathology easily misdiagnosed. Thus, any isolated unilateral process in the paranasal sinuses with long-existing symptoms must be given careful attention due to the chance of this process being an inverted papilloma with malignization. CT scan indicating a unilateral opacification of paranasal sinuses with local calcifications is a typical manifestation, and endoscopic sphenoidotomy can be recommended as a treatment of choice.

Using thermal effect of 970 nm diode laser to reduce nasal swell body.

In recent decades, semiconductor lasers have been successfully used in rhinology. However, their usage in the reduction of the nasal swell body (NSB) is barely studied. Our research aimed to conduct an experimental selection of the laser exposure mode in the NSB zone using a 970 nm diode laser for safe and effective NSB reduction. The thermometric parameters of a diode laser with a wavelength of 970 nm were evaluated in a continuous contact mode of exposure at the power from 2 W to 10 W with 2 W step. The laser was targeted at the liver of cattle, given its similar optical properties to the NSB region. After a series of experiments with every power rate and the analysis of temperature data, we estimated an optimal exposure mode at a power of 4 W. The collected thermometric data demonstrate the safety of this mode in a clinical setting for NSB reduction due to causing no thermal damage to the adjacent tissue. Based on the experiment, a technique for laser reduction of the NSB was developed to improve nasal breathing in patients with severe hypertrophy of this area. The proposed technique was applied to 39 patients with chronic vasomotor rhinitis and the NSB. All patients were divided into 2 groups. Group 1 consisted of 20 patients who underwent surface contact laser-turbinectomy and the NSB reduction using a 970 nm diode laser. Group 2 included 19 patients with the same pathology who underwent laser-turbinectomy, without reduction of the NSB. No statistically significant difference was observed during the dynamic observation with an objective assessment of nasal respiration according to active anterior rhinomanometry when comparing these subgroups with each other according to the t-criterion for independent samples (p > 0.05). As a result of comparing the data obtained on the NOSE scale using the Student's t-test, a statistically significant difference is observed (p < 0.001). Thus, patients who did not perform the reduction of the NSB subjectively noted the insufficiency of nasal breathing. This fact indicates that the NSB is involved in the regulation of airflow.

Toward Development of a Label-Free Detection Technique for Microfluidic Fluorometric Peptide-Based Biosensor Systems.

The problems of chronic or noncommunicable diseases (NCD) that now kill around 40 million people each year require multiparametric combinatorial diagnostics for the selection of effective treatment tactics. This could be implemented using the biosensor principle based on peptide aptamers for spatial recognition of corresponding protein markers of diseases in biological fluids. In this paper, a low-cost label-free principle of biomarker detection using a biosensor system based on fluorometric registration of the target proteins bound to peptide aptamers was investigated. The main detection principle considered includes the re-emission of the natural fluorescence of selectively bound protein markers into a longer-wavelength radiation easily detectable by common charge-coupled devices (CCD) using a specific luminophore. Implementation of this type of detection system demands the reduction of all types of stray light and background fluorescence of construction materials and aptamers. The latter was achieved by careful selection of materials and design of peptide aptamers with substituted aromatic amino acid residues and considering troponin T, troponin I, and bovine serum albumin as an example. The peptide aptamers for troponin T were designed in silico using the «Protein 3D¼ (SPB ETU, St. Petersburg, Russia) software. The luminophore was selected from the line of ZnS-based solid-state compounds. The test microfluidic system was arranged as a flow through a massive of four working chambers for immobilization of peptide aptamers, coupled with the optical detection system, based on thick film technology. The planar optical setup of the biosensor registration system was arranged as an excitation-emission cascade including 280 nm ultraviolet (UV) light-emitting diode (LED), polypropylene (PP) UV transparent film, proteins layer, glass filter, luminophore layer, and CCD sensor. A laboratory sample has been created.

Study of the Fabrication Technology of Hybrid Microfluidic Biochips for Label-Free Detection of Proteins.

A study of the peculiarities and a comparative analysis of the technologies used for the fabrication of elements of novel hybrid microfluidic biochips for express biomedical analysis have been carried out. The biochips were designed with an incorporated microfluidic system, which enabled an accumulation of the target compounds in a biological fluid to be achieved, thus increasing the biochip system's sensitivity and even implementing a label-free design of the detection unit. The multilevel process of manufacturing a microfluidic system of a given topology for label-free fluorometric detection of protein structures is presented. The technological process included the chemical modification of the working surface of glass substrates by silanization using (3-aminopropyl) trimethoxysilane (APTMS), formation of the microchannels, for which SU-8 technologies and a last generation dry film photoresist were studied and compared. The solid-state phosphor layers were deposited using three methods: drop application; airbrushing; and mechanical spraying onto the adhesive surface. The processes of sealing the system, installing input ports, and packaging using micro-assembly technologies are described. The technological process has been optimized and the biochip was implemented and tested. The presented system can be used to design novel high-performance diagnostic tools that implement the function of express detection of protein markers of diseases and create low-power multimodal, highly intelligent portable analytical decision-making systems in medicine.

Intraoperative Sphenoid Sinus Volume Measurement as an Alternative Technique to Intraoperative Computer Tomography.

Isolated sphenoid sinus disease (ISSD) is where there is a group of pathologies characterized by inflammation in one or both sphenoid sinuses. Although computer tomography (CT)-based 3D reconstruction remains the gold standard among noninvasive approaches to ISSD diagnostics, no standardized techniques for direct intraoperative measurements of the sphenoid sinus volume in ISSD patients have been documented. We suggest a novel technique for the intraoperative measurement of the sphenoid sinus volume. Our technique is based on filling the sinus with 0.01% methylene blue solution after an endoscopic endonasal sphenoidotomy. The proposed technique was applied to 40 ISSD patients during surgery. Obtained intraoperative measurements were compared to noninvasive measurements from 3D reconstructions based on preoperative CT scans. Our results demonstrated that the obtained measurements did not exhibit significant differences exceeding 0.4 cm3, with CT-scan-based measurements in 39 out of 40 cases (p < 10-6, Wilcoxon sign-rank nonparametric test), thus confirming the accuracy of the proposed technique. Disagreements between direct intraoperative and CT-based measurements in a single case have been attributed to the presence of remaining pathological masses in the sinus, which was further confirmed during the secondary check of the operated sinus. Accordingly, we suggest that the agreement between the CT-based and intraoperative volume measurements can be used as an indicator of the successful elimination of all pathological masses from the sinus without having to perform an adequate exposure of the entire sphenoid sinus to reduce intraoperative bleeding. The proposed technique is accurate and does not require the involvement of specialized intraoperative CT scanners and avoids additional radiation exposure for the patient during an additional postoperation CT scan to confirm the success of the surgery.

Computational Analysis of Movement Patterns of Dogs with ADHD-Like Behavior.

Computational approaches were called for to address the challenges of more objective behavior assessment which would be less reliant on owner reports. This study aims to use computational analysis for investigating a hypothesis that dogs with ADHD-like (attention deficit hyperactivity disorder) behavior exhibit characteristic movement patterns directly observable during veterinary consultation. Behavioral consultations of 12 dogs medically treated due to ADHD-like behavior were recorded, as well as of a control group of 12 dogs with no reported behavioral problems. Computational analysis with a self-developed tool based on computer vision and machine learning was performed, analyzing 12 movement parameters that can be extracted from automatic dog tracking data. Significant differences in seven movement parameters were found, which led to the identification of three dimensions of movement patterns which may be instrumental for more objective assessment of ADHD-like behavior by clinicians, while being directly observable during consultation. These include (i) high speed, (ii) large coverage of space, and (iii) constant re-orientation in space. Computational tools used on video data collected during consultation have the potential to support quantifiable assessment of ADHD-like behavior informed by the identified dimensions.

The Effects of Padé Numerical Integration in Simulation of Conservative Chaotic Systems.

In this paper, we consider nonlinear integration techniques, based on direct Padé approximation of the differential equation solution, and their application to conservative chaotic initial value problems. The properties of discrete maps obtained by nonlinear integration are studied, including phase space volume dynamics, bifurcation diagrams, spectral entropy, and the Lyapunov spectrum. We also plot 2D dynamical maps to enlighten the features introduced by nonlinear integration techniques. The comparative study of classical integration methods and Padé approximation methods is given. It is shown that nonlinear integration techniques significantly change the behavior of discrete models of nonlinear systems, increasing the values of Lyapunov exponents and spectral entropy. This property reduces the applicability of numerical methods based on Padé approximation to the chaotic system simulation but it is still useful for construction of pseudo-random number generators that are resistive to chaos degradation or discrete maps with highly nonlinear properties.