Alginate, a naturally occurring biopolymer derived from brown seaweed, is employed in different biomedical applications due to its gel-forming properties. Another attractive materials for bone tissue engineering are the bioactive glasses due to their bioactivity. Thus, the bioactive, biocompatible, and biodegradable characteristics of these biomaterials can be tested to facilitate cell proliferation and osteogenic differentiation in a bioink for bone regeneration. Therefore, the objective of this study was to evaluate the physicochemical characteristics of the materials and the biocompatibility of alginate with the bioactive glass 80SiO2–15CaO–5P2O5 (BG-2B) for application in bone tissue regeneration. An MTT assay was conducted to assess the mitochondrial metabolism of mesenchymal stem cells derived from the pulp of the deciduous teeth in the presence of 6% sodium alginate cross-linked with calcium chloride and BG-2B at concentrations of 0.1, 1, and 10% after 5 days. The zeta potential measured for BG-2B was around -13 mV, and for alginate, it was -44 mV. This indicates that BG-2B is less stable than alginate in suspension, since values of ±10–20 mV are classified as relatively stable and values greater than ±30 mV are classified as highly stable. The viability data indicated that the samples with lower BG-2B concentrations (0.1 and 1%) in alginate had no significant effect in comparison to the control sample (p≥0.05). However, when BG-2B was added at a concentration of 10%, a negative effect on cell viability was observed after a five-day exposure period (p≤0.05), indicating cytotoxicity. In conclusion, the combination of alginate and BG-2B in concentrations of 0.1% and 1% exhibits no cytotoxic effects. It can thus be concluded that the low concentrations of bioceramics have the potential for use in bone regeneration.

Acknowledge: The Office of Naval Research Global (ONRG Award N62909-21-1-2026); National Institute of Science and Technology for Regenerative Medicine (INCT-Regenera); Stem Cell Research Institute (IPCT).

Introduction: The blood–brain barrier (BBB) serves as a critical defence mechanism, protecting the brain from harmful substances. This protective layer is a selective, semi-permeable membrane that restricts the passage of most compounds, allowing only a limited range of substances to traverse it. The optical properties of carbon quantum dots (CQDs) render them exceptional tools for bioimaging applications. Zebrafish, as an important animal model, share significant physiological and genetic similarities with mammals, particularly humans. In this study, CQDs are employed for the bioimaging of zebrafish brains, demonstrating their utility in neurobiological research.

Methods: CQDs were prepared from caffeic acid using the hydrothermal method for 4 hours. The morphological characterization and optical properties of the CQDs were evaluated. The synthesized CQDs were injected into zebrafish and incubated for 24 and 48 hours. Post incubation, the zebrafish were sacrificed and brain sections were observed under epifluorescence microscope.

Results and discussion: The morphological , chemical, and optical characterization of CQD confirms the synthesis of CQDs with photoluminescence properties. Zebrafish brain sections were observed under an epifluorescence microscope, allowing for the detailed visualization of the fluorescence within the neural tissue. Moreover, our findings demonstrate that CQDs successfully traversed the blood–brain barrier (BBB), evidenced by their presence within the brain of the zebrafish specimens.

Conclusion: The detailed visualization of zebrafish brain sections demonstrated the presence of CQDs within the neural tissue, validating their capability to cross the highly selective blood–brain barrier (BBB). This finding highlights the potential of CQDs for applications in neurobiological research and therapeutic strategies. The promising results of this study lay a foundation for the development of CQD-based applications in the realms of neuroscience, diagnostics, and nanomedicine.

Introduction: Surface functionalization serves as a keystone for tailoring the properties of carbon quantum dots (CQDs). This strategy allows for precise control over their functionality, ultimately dictating their performance in biocompatibility and targeted applications. SuFEx functionalization of CQD allows for the quick installation of S(VI)F motifs as connective linkers to various functional arms, creating a sulfur hub on the tailored CQD surface. The SuFEx click reaction, being metal catalyst-free, is suitable for bioconjugation where traditional Cu-based click reactions fail. The current research explores the antibacterial activity of SuFEx-functionalized CQD against Gram-positive and Gram-negative bacterial strains.

Methods: CQDs were synthesized under mild hydrothermal conditions from molasses under autogenous pressure for 4 h, filtered, and dried. The as-synthesized CQD were SuFEx functionalized using [4-(Acetylamino)phenyl]-ImidodiSulfuryl diFluoride (AISF) at room temperature and purified by silica gel chromatography. The antibacterial activity of functionalized CQD was evaluated by qualitative and quantitative antibacterial assays.

Results and Discussion: In this study, we synthesized and investigated antibacterial activity against prominent bacterial strains, Escherichia coli and Staphylococcus aureus. Employing in vitro experimentation, we assessed the antibacterial efficiency of these materials.

Conclusions: This work effectively synthesized novel materials and assessed their antibacterial efficacy against Escherichia coli and Staphylococcus aureus in vitro. The findings on their efficiency against these well-known bacterial strains will assist in the development of prospective antimicrobial agents.

Introduction: Medical diagnostics have been transformed via the incorporation of artificial intelligence (AI) into signal processing, which has greatly enhanced the analysis of intricate biomedical data. This review investigates how AI improves medical imaging diagnoses. Methods: A review of the literature was carried out to find the latest developments in AI signal processing applications in the medical imaging field. Techniques such as data fusion, deep learning, and machine learning were assessed based on their diagnostic utility, accuracy, and precision. Results and Discussion: AI has greatly improved the way that Magnetic Resonance Imaging (RMI) and Computed Tomography (CT) signals are processed, making it possible to analyze high-dimensional biomedical data more precisely and effectively. Convolutional neural networks have demonstrated up to 97% segmentation accuracy in brain tumor identification, which greatly facilitates early diagnosis and treatment planning. Generative adversarial networks have enhanced denoising and picture resolution, making it easier to identify minute anomalies in medical imaging. Precise tissue distinction has been made possible by AI-driven segmentation techniques, which are essential for the diagnosis of cancers and neurological disorders. In CT scans, for instance, AI algorithms have attained a 94% accuracy rate in identifying benign tumors from malignant lung lesions. AI-enhanced MRI has also improved the imaging of intricate anatomical components, which helps with the accurate diagnosis of musculoskeletal disorders and cardiovascular diseases. Additionally, early disease diagnosis and therapy planning have been enhanced by AI-driven signal processing. AI systems have proven to be able to cut the number of false positives in cancer detection by 50%, which increases diagnostic confidence and lowers the number of needless biopsies. Conclusions: AI-driven developments in image segmentation and signal processing have improved the precision of diagnoses and made customized treatment plans possible. Further advancements in research and technology progress are expected to augment the efficacy of these techniques in clinical settings.

Background: Restoring functionality to abdominal wall defects is a key challenge in reconstructive surgery. It is estimated that over 700,000 abdominal wall reconstructions are conducted annually in the United States, with more than 20 million performed worldwide each year. Synthetic grafts and crosslinked, animal-derived biological grafts often lead to significant adverse reactions following implantation. This study aimed to assess the effectiveness of a decellularization protocol in producing a fully acellular, full-thickness abdominal wall scaffold, an alternative therapeutic application for abdominal wall reconstruction. Methods: Full-thickness abdominal wall samples were harvested from Wistar rats and submitted to a three-cycle decellularization process. Histological, biochemical, and DNA quantification analyses were applied. In addition, implantation of decellularized abdominal wall scaffolds was performed at the scapular region of Sprague Dawley rats. The grafts remained for 4 weeks and were then explanted; histological analysis utilizing Hematoxylin and Eosin and immunohistochemistry against CD11b (macrophages), CD4 (T-helper cells), and CD8 (cytotoxic T cells) were performed to assess the biocompatibility potential. Results: Histological, biochemical, and DNA analysis results showed efficient decellularization of the abdominal wall samples after the third cycle. Decellularized abdominal wall scaffolds were characterized by good biochemical and mechanical properties. Biocompatibility assessment showed the successful migration of the host’s cells to the implanted abdominal wall scaffolds. Furthermore, no presence of CD11b, CD4, or CD8 cells was observed in the grafts after 4 weeks of implantation. Conclusion: The data presented herein confirm the effective production of a rat-derived, full-thickness abdominal wall scaffold. In addition, the scaffold was biocompatible after a 4-week implantation period. Expanding this approach will allow the exploitation of the capacity of the proposed decellularization protocol in producing acellular abdominal wall scaffolds from larger animal models or human cadaveric donors.

Introduction: The creation of new sustainable methods that can maintain optimal oxygen levels in hydrogel scaffolds containing algal biomass is essential for regenerative medicine. Autotrophic tissue engineering utilises photosynthesis to harness the biological ability of algae to create oxygen in tissue constructs capable of self-sustenance, minimising reliance on external nutrient sources. We embedded polymeric hydrogels with algal biomass of Scenedesmus obliquus, which improved their wound healing ability in mouse models.

Method: Algal biomass (Scenedesmus obliquus) was added into the monomer mixture of acrylic acid(AA) and N-[3-(dimethylamino)propyl]-methacrylamide (DMAPMA) along with ammonium persulphate (APS), and N,N,N′,N′-tetramethyl ethylenediamine (TEMED) for the synthesis of algal biomass-loaded hydrogel scaffolds through free radical aqueous copolymerisation. Further, this algal biomass-loaded hydrogel scaffold was tested for excisional cutaneous wound healing in BALB/c mice models for 14 days.

Result and Discussion: Algal hydrogel scaffolds with varying concentrations of Scenedesmus obliquus were applied for 14 days to excisional wounds in BALB/c mice. It was observed that algal hydrogel scaffolds promoted accelerated wound healing and had significant anti-inflammatory properties.

Conclusions: The results obtained suggest that infusing algal biomass into the polymer matrix improves wound healing ability and provides a pathway for the development of novel potential biomaterials for wound healing therapy.

Introduction: Biosensors are instruments capable of providing quantitative or semi-quantitative analytical information from an identifier in the form of a bioreceptor linked to signal transduction. Nanosized hydroxyapatite (nHA) is often used as an immobilisation matrix component due to its excellent biocompatibility and high adsorption capacity. Successful immobilisation of bioreceptor molecules on the surface of the working electrode is the key to achieving high sensitivity of the biosensor. To achieve better binding of biomolecules to the nHA matrix, plasma chemical surface modification is used in the present work.

Methods: The synthesis of nHA was carried out by the chemical precipitation method. The obtained powder was characterised by XRD, FTIR, TEM, and BET, and the zeta potential was measured. To study the adsorption properties and surface modification, the nHA powder was pressed into 10 mm diameter tablets. To obtain carboxyl functional groups on the surface of the material, a perfected mode of plasma deposition from CO₂/C₂H₄/Ar gas mixture on a ZP-COVANCE-RFPE-3MP unit was used. The treated materials were investigated by SEM, EDX analysis, XPS, and WCA. The adsorption capacity was investigated using glucose oxidase enzyme as an example. Cross-linking by carbodiimide chemistry was carried out to immobilise glucose oxidase.

Results: Plasma modification resulted in successful immobilisation of glucose oxidase on the nHA surface. According to XPS data, the spectra obtained indicated the presence of carboxyl compounds on the surface of the modified samples. Plasma chemical treatment was shown to increase the bond strength between the nHA substrate and immobilised glucose oxidase molecules.

Conclusions: An approach to immobilise biomolecules on hydroxyapatite matrix has been developed, which is promising for applications in biosensors.

Funding: This work was supported by the Russian Science Foundation (grant №20-19-00120-P).

This study focused on classifying large sets of Optical Coherence Tomography (OCT) retinal fundus images into categories indicative of either healthy retinas or those affected by diabetic retinopathy. To achieve accurate classification, this study employed advanced feature extraction methods, specifically the Gray Level Run Length Matrix (GLRLM), the Gray Level Co-Occurrence Matrix (GLCM), and Gray Level Histogram Features (GLHFs). These techniques are crucial for capturing detailed textures and patterns within the retinal images, which are instrumental in distinguishing between healthy and disease-affected tissues. A total of 301 color OCT retinal fundus images were analyzed in this research. These images were sourced from both healthy individuals and those diagnosed with diabetic retinopathy, providing a comprehensive dataset for evaluation. To enhance the quality of the images and improve the accuracy of the feature extraction, a fourth-order Partial Differential Equation (PDE) filter was applied during the image pre-processing phase. This filtering step aimed to reduce noise and enhance the structural features in the images. The primary objective of this study was to identify the most effective feature extraction technique for differentiating between healthy and diabetic retinopathy-affected retinas. By comparing the performance of the GLRLM, the GLCM, and GLHFs, this study sought to determine which method offers the most reliable results in retinal disease classification, thus contributing to better diagnostic tools and methodologies in ophthalmology.

Three-dimensional (3D) bioprinting combines biomimetic materials and cells to promote the functional recovery of tissues and organs. This technique can be applied to overcome challenges in the regeneration of tissues with a poor intrinsic regeneration capacity, such as the nervous tissue. In this context, the aim of this study was to produce a bioink using rat Decellularized Spinal Cord Tissue (DSCT) and mesenchymal cells (MSCs) for nervous tissue 3D bioprinting. The bioink was produced with 1.5% DSCT, 3% gelatin, 4% alginate, 0.1 mg/mL PEDOT:PSS, a conductive polymer, and 1X106 MSC/mL. MSCs were isolated from human deciduous teeth and were characterized using flow cytometry. The material physical properties were evaluated using electrical conductivity measurements, rheological characterization, and scanning electron microscopy (SEM). The swelling ratio and degradation were analyzed for a duration of 4 weeks. Cell viability was analyzed using MTT and live/dead assays. The bioprinted cells were submitted to a neural differentiation protocol and neural markers were analyzed using flow cytometry. The isolated cells were positively identified as MSCs by characteristic stem cell markers. The addition of PEDOT:PSS to the hydrogel increased its electrical conductivity. The hydrogel presented shear thinning behavior and a low G’’/G’ ratio, allowing for good printability without significantly compromising cell viability. SEM images showed a highly porous three-dimensional structure. The hydrogel reached its peak swelling ration at week 1 after printing and lost 24% of its weight at week 2, maintaining a constant weight until week 4. The MTT assay on day 1 indicated no viability reduction compared to the control. The live/dead assay showed more than 75% cell viability at the week 1 timepoint. Flow cytometry indicated an increased ꞴIII-tubulin and glial fibrillary acidic protein expression. The data mentioned above indicate that the bioink holds great promise as an easily available biomaterial for neural tissue engineering via 3D bioprinting.

Introduction:

Brain--computer interface (BCI) systems aim to transmit control commands generated through brain activity to computer applications. Mastery of BCIs generally requires special training, in which some of the users (the so-called BCI-illiterates) might be lacking. Our research paper examines the relation between the users’ individual mental rotation abilities and the effort associated with mastering motor-imagery-based BCI systems.

Methods:

The mental rotation abilities in the test subjects were assessed with a dedicated test that complies with the paradigm developed by Vandenberg and Kuse. The number of correct answers on 3D figure rotations provided during the 90 seconds allocated for the test was recorded. Subsequently, the subjects were asked to control a robotic claw arm to transfer cubes from one place to another, within the motor imagination BCI paradigm. To reflect the BCI learning effort and effectiveness, the number of cubes transferred and the average time to transfer one cube were recorded.

Results and Discussion:

We report on the positive relation between the individual mental 3D rotation abilities and the mastery of motor imagery BCI system. Then we put forward and discuss the ensuing recommendations for organizing effective and time-efficient training for this BCI-illiterate category of users. Particularly, we propose using a brain model topographic map of the subjects’ EEG to visualize the feedback during the training process.

Conclusions:

BCI illiteracy is one of the biggest challenges for the wider adoption of effective BCI systems that have the potential to improve life quality and experience for many users. The reported relation is a step forward towards both understanding the causes of this phenomenon and the design of successful training programs. One way to mitigate BCI illiteracy might be through 3D figure mental rotation training, but this necessitates further research.