It takes two to attach - endo-1,3-ß-d-glucanase as a potential receptor of mannose-independent, FimH-dependent Salmonella Typhimurium binding to spinach leaves.

Currently, fresh, unprocessed food has become a relevant element of the chain of transmission of enteropathogenic infections. To survive on a plant surface and further spread the infections, pathogens like Salmonella have to attach stably to the leaf surface. Adhesion, driven by various virulence factors, including the most abundant fim operon encoding type 1 fimbriae, is usually an initial step of infection, preventing physical removal of the pathogen. Adhesion properties of Salmonella's type 1 fimbriae and its FimH adhesin were investigated intensively in the past. However, there is a lack of knowledge regarding its role in interaction with plant cells. Understanding the mechanisms and structures involved in such interaction may facilitate efforts to decrease the risk of contamination and increase fresh food safety. Here, we applied Salmonella genome site-directed mutagenesis, adhesion assays, protein-protein interactions, and biophysics methods based on surface plasmon resonance to unravel the role of FimH adhesin in interaction with spinach leaves. We show that FimH is at least partially responsible for Salmonella binding to spinach leaves, and this interaction occurs in a mannose-independent manner. Importantly, we identified a potential FimH receptor as endo-1,3-ß-d-Glucanase and found that this interaction is strong and specific, with a dissociation constant in the nanomolar range. This research advances our comprehension of Salmonella's interactions with plant surfaces, offering insights that can aid in minimizing contamination risks and improving the safety of fresh, unprocessed foods.

Salmonella adhesion is decreased by hypoxia due to adhesion and motility structure crosstalk.

Initial stages of Salmonella Typhimurium infection involve a series of coordinated events aimed at reaching, attaching to, and invading host cells. Virulence factors such as flagella, fimbriae, and secretion systems play crucial roles in these events and are regulated in response to the host environment. The first point of contact between the pathogen and host is the intestinal epithelial layer, which normally serves as a barrier against invading pathogens, but can also be an entry site for pathogens. The integrity of this barrier can be modulated by the hypoxic environment of the intestines, created by the presence of trillions of microbes. Variable oxygen concentrations can strongly affect many functions of the gut, including secretion of cytokines and growth factors from the host site and affect the ability of Salmonella to persist, invade, and replicate. In this study, we investigated the first stages of Salmonella Typhimurium infection under hypoxic conditions in vitro and found that low oxygen levels significantly decreased bacterial adhesion. Using adhesion and motility assays, biofilm formation tests, as well as gene expression and cytokine secretion analysis, we identified a hypoxia-specific cross-talk between the expression of type 1 fimbriae and flagella, suggesting that altered flagellin expression levels affect the motility of bacteria and further impact their adhesion level, biofilm formation ability, and innate immune response. Overall, understanding how Salmonella interacts with its variable host environment provides insights into the virulence mechanisms of the bacterium and information regarding strategies for preventing or treating infections. Further research is required to fully understand the complex interplay between Salmonella and its host environment.

Computer-Aided Diagnosis Methods for High-Frequency Ultrasound Data Analysis: A Review.

Over the last few decades, computer-aided diagnosis systems have become a part of clinical practice. They have the potential to assist clinicians in daily diagnostic tasks. The image processing techniques are fast, repeatable, and robust, which helps physicians to detect, classify, segment, and measure various structures. The recent rapid development of computer methods for high-frequency ultrasound image analysis opens up new diagnostic paths in dermatology, allergology, cosmetology, and aesthetic medicine. This paper, being the first in this area, presents a research overview of high-frequency ultrasound image processing techniques, which have the potential to be a part of computer-aided diagnosis systems. The reviewed methods are categorized concerning the application, utilized ultrasound device, and image data-processing type. We present the bridge between diagnostic needs and already developed solutions and discuss their limitations and future directions in high-frequency ultrasound image analysis. A search was conducted of the technical literature from 2005 to September 2022, and in total, 31 studies describing image processing methods were reviewed. The quantitative and qualitative analysis included 39 algorithms, which were selected as the most effective in this field. They were completed by 20 medical papers and define the needs and opportunities for high-frequency ultrasound application and CAD development.

High-Frequency Ultrasound Dataset for Deep Learning-Based Image Quality Assessment.

This study aims at high-frequency ultrasound image quality assessment for computer-aided diagnosis of skin. In recent decades, high-frequency ultrasound imaging opened up new opportunities in dermatology, utilizing the most recent deep learning-based algorithms for automated image analysis. An individual dermatological examination contains either a single image, a couple of pictures, or an image series acquired during the probe movement. The estimated skin parameters might depend on the probe position, orientation, or acquisition setup. Consequently, the more images analyzed, the more precise the obtained measurements. Therefore, for the automated measurements, the best choice is to acquire the image series and then analyze its parameters statistically. However, besides the correctly received images, the resulting series contains plenty of non-informative data: Images with different artifacts, noise, or the images acquired for the time stamp when the ultrasound probe has no contact with the patient skin. All of them influence further analysis, leading to misclassification or incorrect image segmentation. Therefore, an automated image selection step is crucial. To meet this need, we collected and shared 17,425 high-frequency images of the facial skin from 516 measurements of 44 patients. Two experts annotated each image as correct or not. The proposed framework utilizes a deep convolutional neural network followed by a fuzzy reasoning system to assess the acquired data's quality automatically. Different approaches to binary and multi-class image analysis, based on the VGG-16 model, were developed and compared. The best classification results reach 91.7% accuracy for the first, and 82.3% for the second analysis, respectively.

The Assessment of Activity of Antiseptic Agents against Biofilm of Staphylococcus aureus Measured with the Use of Processed Microscopic Images.

Staphylococcal biofilms are major causative factors of non-healing wound infections. Their treatment algorithms recommend the use of locally applied antiseptic agents to counteract the spread of infection. The efficacy of antiseptics against biofilm is assessed in vitro by a set of standard quantitative and semi-quantitative methods. The development of software for image processing additionally allowed for the obtainment of quantitative data from microscopic images of biofilm dyed with propidium iodine and SYTO-9 reagents, differentiating dead cells from live ones. In this work, the method of assessment of the impact of antiseptic agents on staphylococcal biofilm in vitro, based on biofilms' processed images, was proposed and scrutinized with regard to clinically relevant antiseptics, polyhexanide, povidone-iodine and hypochlorite. The standard quantitative culturing method was applied to validate the obtained data from processed images. The results indicated significantly higher activity of polyhexanide and povidone-iodine than hypochlorite against staphylococcal biofilm. Taking into account the fact that in vitro results of the efficacy of antiseptic agents against staphylococcal biofilm are frequently applied to back up their use in hospitals and ambulatory units, our work should be considered an important tool; providing reliable, quantitative data in this regard.

Deep Learning-Based High-Frequency Ultrasound Skin Image Classification with Multicriteria Model Evaluation.

This study presents the first application of convolutional neural networks to high-frequency ultrasound skin image classification. This type of imaging opens up new opportunities in dermatology, showing inflammatory diseases such as atopic dermatitis, psoriasis, or skin lesions. We collected a database of 631 images with healthy skin and different skin pathologies to train and assess all stages of the methodology. The proposed framework starts with the segmentation of the epidermal layer using a DeepLab v3+ model with a pre-trained Xception backbone. We employ transfer learning to train the segmentation model for two purposes: to extract the region of interest for classification and to prepare the skin layer map for classification confidence estimation. For classification, we train five models in different input data modes and data augmentation setups. We also introduce a classification confidence level to evaluate the deep model's reliability. The measure combines our skin layer map with the heatmap produced by the Grad-CAM technique designed to indicate image regions used by the deep model to make a classification decision. Moreover, we propose a multicriteria model evaluation measure to select the optimal model in terms of classification accuracy, confidence, and test dataset size. The experiments described in the paper show that the DenseNet-201 model fed with the extracted region of interest produces the most reliable and accurate results.

The Co-Culture of Staphylococcal Biofilm and Fibroblast Cell Line: The Correlation of Biological Phenomena with Metabolic NMR1 Footprint.

Staphylococcus aureus is one of the most prevalent pathogens associated with several types of biofilm-based infections, including infections of chronic wounds. Mature staphylococcal biofilm is extremely hard to eradicate from a wound and displays a high tendency to induce recurring infections. Therefore, in the present study, we aimed to investigate in vitro the interaction between S. aureus biofilm and fibroblast cells searching for metabolites that could be considered as potential biomarkers of critical colonization and infection. Utilizing advanced microscopy and microbiological methods to examine biofilm formation and the staphylococcal infection process, we were able to distinguish 4 phases of biofilm development. The analysis of staphylococcal biofilm influence on the viability of fibroblasts allowed us to pinpoint the moment of critical colonization-12 h post contamination. Based on the obtained model we performed a metabolomics analysis by 1H NMR spectroscopy to provide new insights into the pathophysiology of infection. We identified a set of metabolites related to the switch to anaerobic metabolism that was characteristic for staphylococcal biofilm co-cultured with fibroblast cells. The data presented in this study may be thus considered a noteworthy but preliminary step in the direction of developing a new, NMR-based tool for rapid diagnosing of infection in a chronic wound.

Potential of Bacterial Cellulose Chemisorbed with Anti-Metabolites, 3-Bromopyruvate or Sertraline, to Fight against Helicobacter pylori Lawn Biofilm.

Helicobacter pylori is a bacterium known mainly of its ability to cause persistent inflammations of the human stomach, resulting in peptic ulcer diseases and gastric cancers. Continuous exposure of this bacterium to antibiotics has resulted in high detection of multidrug-resistant strains and difficulties in obtaining a therapeutic effect. The purpose of the present study was to determine the usability of bacterial cellulose (BC) chemisorbed with 3-bromopyruvate (3-BP) or sertraline (SER) to act against lawn H. pylori biofilms. The characterization of BC carriers was made using a N2 adsorption/desorption analysis, tensile strength test, and scanning electron microscopy (SEM) observations. Determination of an antimicrobial activity was performed using a modified disk-diffusion method and a self-designed method of testing antibacterial activity against biofilm microbial forms. In addition, bacterial morphology was checked by SEM. It was found that BC disks were characterized by a high cross-linking and shear/stretch resistance. Growth inhibition zones for BC disks chemisorbed with 2 mg of SER or 3-BP were equal to 26.5-27.5 mm and 27-30 mm, respectively. The viability of lawn biofilm H. pylori cells after a 4-h incubation with 2 mg SER or 3-BP chemisorbed on BC disks was ≥4 log lower, suggesting their antibacterial effect. SEM observations showed a number of morphostructural changes in H. pylori cells exposed to these substances. Concluding, SER and 3-BP chemisorbed on BC carriers presented a promising antibacterial activity against biofilm H. pylori cells in in vitro conditions.

Novel (S)-1,3,4,12a-tetrahydropyrazino[2,1-c][1,4]benzodiazepine-6,12(2H,11H)-dione derivatives: Selective inhibition of MV-4-11 biphenotypic B myelomonocytic leukemia cells' growth is accompanied by reactive oxygen species overproduction and apoptosis.

A series of optically pure (R)- and (S)-1,3,4,12a-tetrahydropyrazino[2,1-c][1,4]benzodiazepine-6,12(2H,11H)-dione derivatives was designed and synthesized as novel anthramycin analogues in a three-step, one-pot procedure, and tested for their antiproliferative activity on nine following cell lines: MV-4-11, UMUC-3, MDA-MB-231, MCF7, LoVo, HT-29, A-549, A2780 and BALB/3T3. The key structural features responsible for exhibition of cytotoxic effect were determined: the (S)-configuration of chiral center and the presence of hydrophobic 4-biphenyl substituent in the side chain. Introduction of bromine atom into the 8 position (8g) or substitution of dilactam ring with benzyl group (8m) further improved the activity and selectivity of investigated compounds. Among others, compound 8g exhibited selective cytotoxic effect against MV-4-11 (IC50 = 8.7 µM) and HT-29 (IC50 = 17.8 µM) cell lines, while 8m showed noticeable anticancer activity against MV-4-11 (IC50 = 10.8 µM) and LoVo (IC50 = 11.0 µM) cell lines. The cell cycle arrest in G1/S checkpoint and apoptosis associated with overproduction of reactive oxygen species was also observed for 8e and 8m.

High-frequency ultrasound in anti-aging skin therapy monitoring.

Over the last few decades, high-frequency ultrasound has found multiple applications in various diagnostic fields. The fast development of this imaging technique opens up new diagnostic paths in dermatology, allergology, cosmetology, and aesthetic medicine. In this paper, being the first in this area, we discuss the usability of HFUS in anti-aging skin therapy assessment. The fully automated algorithm combining high-quality image selection and entry echo layer segmentation steps followed by the dermal parameters estimation enables qualitative and quantitative evaluation of the effectiveness of anti-aging products. Considering the parameters of subcutaneous layers, the proposed framework provides a reliable tool for TCA-peel therapy assessment; however, it can be successfully applied to other skin-condition-related problems. In this randomized controlled clinical trial, forty-six postmenopausal women were randomly assigned to the experimental and control groups. Women were treated four times at one-week intervals and applied skin cream daily between visits. The three month follow-up study enables measurement of the long-term effect of the therapy. According to the results, the TCA-based therapy increased epidermal (entry echo layer) thickness, indicating that the thinning process has slowed down and the skin's condition has improved. An interesting outcome is the obtained growth in the intensity of the upper dermis in the experimental group, which might suggest a reduced photo-aging effect of TCA-peel and increased water content. The same conclusions connected with the anti-aging effect of TCA-peel can be drawn by observing the parameters describing the contribution of low and medium-intensity pixels in the upper dermis. The decreased share of low-intensity pixels and increased share of medium-intensity pixels in the upper dermis suggest a significant increase in local protein synthesis.

Comparison of antibiofilm activity of low-concentrated hypochlorites vs polyhexanide-containing antiseptic.

Chronic wound infection is highly associated with morbidity and endangers the patient's life. Therefore, wound care products must have a potent antimicrobial and biofilm-eradicating effect. In this work, the antimicrobial/antibiofilm activity of two low-concentrated chlorine-based and releasing solutions was investigated on a total of 78 strains of methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans, using the cohesive spectrum of in vitro settings, including microtiter plate models, biofilm-oriented antiseptic test, cellulose-based biofilm model, biofilm bioreactors and Bioflux model. The antiseptic containing polyhexamethylene biguanide was used in the character of usability control of performed tests. The results obtained by static biofilm models indicate that low-concentrated chlorine-based and releasing solutions display none to moderate antibiofilm activity, while data obtained by means of the Bioflux model, providing flow conditions, indicate the moderate antibiofilm activity of substances compared with the polyhexanide antiseptic. Considering in vitro data presented in this manuscript, the earlier reported favorable clinical results of low-concentrated hypochlorites should be considered rather an effect of their rinsing activity combined with low cytotoxicity but not the antimicrobial effect per se. For the treatment of heavily biofilm-infected wounds, polyhexanide should be considered the agent of choice because of its higher efficacy against pathogenic biofilms.

Automated segmentation of epidermis in high-frequency ultrasound of pathological skin using a cascade of DeepLab v3+ networks and fuzzy connectedness.

This study proposes a novel, fully automated framework for epidermal layer segmentation in different skin diseases based on 75 MHz high-frequency ultrasound (HFUS) image data. A robust epidermis segmentation is a vital first step to detect changes in thickness, shape, and intensity and therefore support diagnosis and treatment monitoring in inflammatory and neoplastic skin lesions. Our framework links deep learning and fuzzy connectedness for image analysis. It consists of a cascade of two DeepLab v3+ models with a ResNet-50 backbone and a fuzzy connectedness analysis module for fine segmentation. Both deep models are pre-trained on the ImageNet dataset and subjected to transfer learning using our HFUS database of 580 images with atopic dermatitis, psoriasis and non-melanocytic skin tumors. The first deep model is used to detect the appropriate region of interest, while the second stands for the main segmentation procedure. We use the softmax layer of the latter twofold to prepare the input data for fuzzy connectedness analysis: as a reservoir of seed points and a direct contribution to the input image. In the experiments, we analyze different configurations of the framework, including region of interest detection, deep model backbones and training loss functions, or fuzzy connectedness analysis with parameter settings. We also use the Dice index and epidermis thickness to compare our results to state-of-the-art approaches. The Dice index of 0.919 yielded by our model over the entire dataset (and exceeding 0.93 in inflammatory diseases) proves its superiority over the other methods.

Deep learning approach to skin layers segmentation in inflammatory dermatoses.

Monitoring skin layers with medical imaging is critical to diagnosing and treating patients with chronic inflammatory skin diseases. The high-frequency ultrasound (HFUS) makes it possible to monitor skin condition in different dermatoses. Accurate and reliable segmentation of skin layers in patients with atopic dermatitis or psoriasis enables the assessment of the treatment effect by the layer thickness measurements. The epidermis and the subepidermal low echogenic band (SLEB) are the most important for further diagnosis since their appearance is an indicator of different skin problems. In medical practice, the analysis, including segmentation, is usually performed manually by the physician with all drawbacks of such an approach, e.g., extensive time consumption and lack of repeatability. Recently, HFUS becomes common in dermatological practice, yet it is barely supported by the development of automated analysis tools. To meet the need for skin layer segmentation and measurement, we developed an automated segmentation method of both epidermis and SLEB layers. It consists of a fuzzy c-means clustering-based preprocessing step followed by a U-shaped convolutional neural network. The network employs batch normalization layers adjusting and scaling the activation to make the segmentation more robust. The obtained segmentation results are verified and compared to the current state-of-the-art methods addressing the skin layer segmentation. The obtained Dice coefficient equal to 0.87 and 0.83 for the epidermis and SLEB, respectively, proves the developed framework's efficiency, outperforming the other approaches.

Chronic wounds multimodal image database.

A multimodal wound image database was created to allow fast development of computer-aided approaches for wound healing monitoring. The developed system with parallel camera optical axes enables multimodal images: photo, thermal, stereo, and depth map of the wound area to be acquired. As a result of using this system a multimodal database of chronic wound images is introduced. It contains 188 image sets of photographs, thermal images, and 3D meshes of the surfaces of chronic wounds acquired during 79 patient visits. Manual wound outlines delineated by an expert are also included in the dataset. All images of each case are additionally coregistered, and both numerical registration parameters and the transformed images are covered in the database. The presented database is publicly available for the research community at https://chronicwounddatabase.eu. That is the first publicly available database for evaluation and comparison of new image-based algorithms in the wound healing monitoring process with coregistered photographs, thermal maps, and 3D models of the wound area. Easily available database of coregistered multimodal data with the raw data set allows faster development of algorithms devoted to wound healing analysis and monitoring.

Gallic Acid Based Black Tea Extract as a Stabilizing Agent in ZnO Particles Green Synthesis.

In this work, zinc oxide particles (ZnO NPs) green synthesis with the application of black tea extract (BT) is presented. A thorough investigation of the properties of the extract and the obtained materials was conducted by using Fourier transform infrared spectroscopy (FTIR), liquid chromatography-mass spectrometry (LC-MS), X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and quadrupole mass spectroscopy (QMS). The obtained results indicated that the amount of used BT strongly influenced the morphology, chemical, and crystalline structure of the obtained particles. The investigation demonstrated that the substance present in black tea (BT) extract, which was adsorbed on the ZnO surface, was in fact gallic acid. It was found that gallic acid controls the crystallization process of ZnO by temporarily blocking the zinc cations. Additionally, these organic molecules interact with the hydroxide group of the precipitant. This blocks the dehydration process stabilizing the zinc hydroxide forms and hinders its transformation into zinc oxide. Performed measurements indicated that obtained ZnO particles have great antioxidant and antimicrobial properties, which are significantly correlated with ZnO-gallic acid interactions.

Automated size-specific dose estimates using deep learning image processing.

An automated vendor-independent system for dose monitoring in computed tomography (CT) medical examinations involving ionizing radiation is presented in this paper. The system provides precise size-specific dose estimates (SSDE) following the American Association of Physicists in Medicine regulations. Our dose management can operate on incomplete DICOM header metadata by retrieving necessary information from the dose report image by using optical character recognition. For the determination of the patient's effective diameter and water equivalent diameter, a convolutional neural network is employed for the semantic segmentation of the body area in axial CT slices. Validation experiments for the assessment of the SSDE determination and subsequent stages of our methodology involved a total of 335 CT series (60 352 images) from both public databases and our clinical data. We obtained the mean body area segmentation accuracy of 0.9955 and Jaccard index of 0.9752, yielding a slice-wise mean absolute error of effective diameter below 2 mm and water equivalent diameter at 1 mm, both below 1%. Three modes of the SSDE determination approach were investigated and compared to the results provided by the commercial system GE DoseWatch in three different body region categories: head, chest, and abdomen. Statistical analysis was employed to point out some significant remarks, especially in the head category.

In Vitro Evaluation of Polihexanide, Octenidine and NaClO/HClO-Based Antiseptics against Biofilm Formed by Wound Pathogens.

Chronic wounds complicated with biofilm formed by pathogens remain one of the most significant challenges of contemporary medicine. The application of topical antiseptic solutions against wound biofilm has been gaining increasing interest among clinical practitioners and scientific researchers. This paper compares the activity of polyhexanide-, octenidine- and hypochlorite/hypochlorous acid-based antiseptics against biofilm formed by clinical strains of Candida albicans, Staphylococcus aureus and Pseudomonas aeruginosa. The analyses included both standard techniques utilizing polystyrene plates and self-designed biocellulose-based models in which a biofilm formed by pathogens was formed on an elastic, fibrinous surface covered with a fibroblast layer. The obtained results show high antibiofilm activity of polihexanide- and octenidine-based antiseptics and lack or weak antibiofilm activity of hypochlorite-based antiseptic of total chlorine content equal to 80 parts per million. The data presented in this paper indicate that polihexanide- or octenidine-based antiseptics are highly useful in the treatment of biofilm, while hypochlorite-based antiseptics with low chlorine content may be applied for wound rinsing but not when specific antibiofilm activity is required.

Computer Aided Diagnosis of Atopic Dermatitis.

Skin diseases with an allergic background such as atopic dermatitis are commonly noticed in children. This requires an urgent need to develop an objective and non-invasive method to examine the skin condition before and during the therapy. The newest clinical research mention the benefit of using high frequency ultrasound to image inflammation of the skin. A characteristic feature of inflammatory dermatoses is the presence of a superficial hypoechoic band below the echo entry in high frequency ultrasound images. Its measurement can be useful in the assessment of atopic dermatitis. To meet this need, this paper presents a novel fully automatic method for the characteristic hypoechoic band segmentation. A three step methodology includes epidermis echo entry layer detection and segmentation and on this basis the segmentation of the sought skin abnormality. The algorithm is dedicated to 75MHz US probe, which enables visualisation of a skin area of a 12mm length and 4mm depth. The accuracy of the proposed framework was verified on 45 clinical images annotated by two independent experts. The obtained results prove the benefits of using the ultrasound-based skin disease assessment framework.

Pectin based banana peel extract as a stabilizing agent in zinc oxide nanoparticles synthesis.

Various amounts of banana peel extract were successfully used as a stabilizing agent in the co-precipitation of zinc oxide nanoparticles. The obtained materials were characterized by means of Fourier transform infrared spectroscopy (FTIR), gel permeation chromatography (GPC), X-ray diffraction (XRD), photoluminescence spectroscopy (PL), scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDS), N2 physisorption, thermogravimetric analysis (TGA), and quadrupole mass spectroscopy (QMS). On account of using such a broad spectrum of analytic methods, a thorough description of the interactions between the organic ingredients of the extract and ZnO particles was presented. It was indicated that the banana peel extract is based on pectin. These carbohydrate macromolecules adsorb on ZnO surface due to presence of active carboxylic groups. By increasing the concentration of polysaccharides, pectin-pectin interactions were also observed. The amount of the extract used for the synthesis significantly influenced the crystalline structure of zinc oxide particles along with their size and morphology. The shape and size were varying from thin flakes (450 × 24 nm) when the smallest amount of the extract was used, through nanocones with pointed tips (210 × 120 nm) agglomerated in a flower-like structure, until cubic-shaped nanoparticles (20-40 nm) agglomerated in a pinecone-like structure (430 × 180 nm) when the biggest amount of the extract was applied. The obtained particles have displayed apromising antimicrobial activity against Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa) bacteria, and fungus (Candida albicans). The highest activity was demonstrated against S. aureus pathogen.

Significant enhancement of citric acid production by Yarrowia lipolytica immobilized in bacterial cellulose-based carrier.

The aim of this study was to improve the yield of citric acid (CA), an industrially valuable metabolite, obtained during Yarrowia lipolytica yeast culturing. To this end, Y. lipolytica cells were immobilized on a novel bacterial cellulose (BC) based carrier and subjected to four subsequent cycles of fed-batch culturing. During the fermentation process, yeasts metabolic stability, glucose consumption and CA production were analyzed. The results of our study have shown that BC-immobilized yeasts utilized more glucose than free cells and that the metabolic activity of BC-immobilized cells and the resultant CA production remained on a stable level throughout 4 fermentation batches, while the drop in free cells' metabolic stability and the consequent drop in CA production was observed with each subsequent batch. Also, the overall concentration of CA product was higher in immobilized vs. free yeasts (121-129 g/L vs. 99-110 g/L, respectively). The presented results indicate that the application of a BC carrier for Y. lipolytica culturing correlates not only with a higher yield of CA product but also with more stable and repeatable conditions of the biotechnological fermentation process. The results obtained in this study may find multiple biotechnological applications in which immobilization of various types of cells is required.