Search Results (209)

Background: MicroRNAs (miRNAs) such as miR-155-5p and miR-221-3p are key regulators of gene expression in cancer. Although both have been implicated in colorectal cancer (CRC) and papillary thyroid carcinoma (PTC), data on their regional expression profiles and clinical associations remain scarce, particularly in the Middle East. This study assessed the expression patterns and clinical relevance of miR-155-5p and miR-221-3p in CRC and PTC patients from Sulaymaniyah Province, Iraq. Methods: Formalin-fixed, paraffin-embedded (FFPE) tumor and adjacent normal tissue samples were collected from 60 CRC patients and 50 PTC patients. miRNA expression levels were quantified using real-time quantitative PCR (RT-qPCR) and analyzed by the ΔΔCt method, adjusted for tumor cellularity. Statistical analyses were conducted to evaluate associations between miRNA expression and clinicopathological parameters. Results: miR-155-5p and miR-221-3p were frequently overexpressed in both CRC (65%) and PTC (72% and 68%, respectively). In CRC, miR-155-5p expression correlated significantly with histological grade, tumor location, and TNM stage (p < 0.05), while miR-221-3p did not show significant associations with clinicopathological features. In PTC, miR-155-5p exhibited a trend toward association with TNM stage (p = 0.02). No significant differences in expression levels of these miRNAs were observed between CRC and PTC samples. Conclusions: Overall, miR-155-5p and miR-221-3p are consistently overexpressed in CRC and PTC, indicating their potential as diagnostic biomarkers. miR-155-5p, in particular, shows promise as a marker of disease progression in CRC. These findings underscore the importance of region-specific studies in advancing our understanding of the molecular landscape of cancer. Full article

Organoids are self-organizing three-dimensional (3D) cellular structures derived from stem cells. They can mimic the anatomical and functional properties of real organs. They have transformed in vitro disease modeling by closely replicating the structural and functional characteristics of human tissues. The complexity and variability of organoid-derived data pose significant challenges for analysis and clinical translation. Artificial Intelligence (AI) has emerged as a crucial enabler, offering scalable and high-throughput tools for interpreting imaging data, integrating multi-omics profiles, and guiding experimental workflows. This review aims to discuss how AI is reshaping organoid-based research by enhancing morphological image analysis, enabling dynamic modeling of organoid development, and facilitating the integration of genomics, transcriptomics, and proteomics for disease classification. Moreover, AI is increasingly used to support drug screening and personalize therapeutic strategies by analyzing patient-derived organoids. The integration of AI with organoid-on-chip systems further allows for real-time feedback and physiologically relevant modeling. Drawing on peer-reviewed literature from the past decade, Furthermore, CNNs have been used to analyze colonoscopy and histopathological images in colorectal cancer with over 95% diagnostic accuracy. We examine key tools, innovations, and case studies that illustrate this evolving interface. As this interdisciplinary field matures, the future of AI-integrated organoid platforms depends on establishing open data standards, advancing algorithms, and addressing ethical and regulatory considerations to unlock their clinical and translational potential. Full article

Late-onset Fuchs endothelial corneal dystrophy (FECD) is a hereditary, progressive, bilateral and irreversible disorder that is characterized by thickening of Descemet’s membrane, microscopic collagenous protuberances known as guttae, and accelerated loss of corneal endothelial cells. Patients initially complain of blurred vision, and as the disease progresses, painful epithelial edema develops. Untreated cases of FECD often result in blindness, and then, the only treatment is corneal transplantation. DNA polymorphisms in many genes have been implicated, among them TCF4 on chromosome 18q, encoding a transcription factor protein E2-2, which is involved in regulating cellular growth and differentiation in the cornea. In our previous published study, we confirmed the association of an intronic TCF4 SNP (rs613872) with the disease in our population. The purpose of this present study is to further investigate another intronic point of interest in the same gene, the CTG18.1 trinucleotide repeat expansion. DNA was isolated from EDTA blood from a well-ascertained group of 36 Greek patients with FECD (Krachmer scale ≥ 2) and 58 healthy individuals, age- and sex-matched after obtaining their informed consent. STR-PCR and triplet-repeat primed PCR (TP-PCR) were performed, followed by gel electrophoresis and fragment analysis on an ABI SeqStudio genetic analyzer. Our real-time qPCR genotyping method was used for the SNP in the LightCycler (Roche). Statistical analysis of both genetic results was performed with SPSS and SNPStats. Full article

The advent of fifth-generation (5G) networks has enabled cellular vehicle-to-everything (C-V2X) communication, requiring the efficient delivery of large volumes of real-time vehicular data under stringent latency and reliability constraints. At the application layer, Message Queuing Telemetry Transport (MQTT) and ZeroMQ have emerged as candidate protocols; however, their comparative performance in vehicular networking contexts remains insufficiently examined. This work presents a simulation-based evaluation of MQTT and ZeroMQ using OMNeT++, integrating INET for protocol modeling, Veins for vehicular mobility, and Simu5G for cellular network operations. We developed custom protocol modules and assessed them under diverse traffic conditions, analyzing key metrics such as end-to-end latency, message overhead, and scalability. Our results reveal that ZeroMQ achieves lower latency in moderate traffic scenarios, whereas MQTT demonstrates superior reliability and efficiency under high traffic loads, offering valuable insights for selecting application-layer protocols in C-V2X environments. Full article

Decabromodiphenyl ether (BDE209) has been widely used because of its excellent flame-retardant properties and ability. On the one hand, many studies have shown that the presence of BDE209 can potentially threaten human health and the environment. The production and processing of products containing BDE209 is prohibited except for special applications in China. On the other hand, the study of BDE209 on respiratory cells is not yet fully understood. Consequently, this study aims to investigate the mechanisms of toxic damage and oxidative stress induced by BDE209 exposure in lung epithelial Beas-2B cells. The proliferation of Beas-2B cells under BDE209 exposure was first analyzed by using a real-time label-free cell analyzer (RTCA). Then the cells’ morphological changes were observed using laser confocal microscopy. Subsequently, the effects of BDE209 exposure alone, combined exposure to N-acetylcysteine (NAC) and BDE209, on reactive oxygen species (ROS) levels and antioxidant defense-related factors in Beas-2B cells were analyzed separately. The results show that BDE209 exposure induces the proliferation of Beas-2B cells with a dose-dependent increase in inhibition. Microscopic observation of Beas-2B cells reveals significant damage and death. The levels of ROS are significantly increased (p < 0.01), the contents of superoxide dismutase (SOD) and malondialdehyde (MDA) are increased, the contents of catalase (CAT) are decreased, and the activities of glutathione peroxidase (GPX) are first decreased and then increased. However, under the co-exposure of NAC and BDE209, ROS levels are significantly reduced (p < 0.01), MDA contents decrease, and SOD activities increase. In summary, BDE209 exposure leads to inhibition of Beas-2B cell proliferation, cellular morphology damage, increased ROS levels, and disturbances in antioxidant defense-related factors. The cells showed toxic damage and oxidative stress. In contrast, NAC can suppress ROS levels, enhance SOD activity, and inhibit GPX activity, thereby alleviating BDE209-induced cellular damage. Full article

Cellular uptake of nanomaterials is based on endocytosis with their endosomal–lysosomal entrapment resulting in enzymatic hydrolysis. Besides biodegradation, the antigen presentation induces innate and adaptive immunity. Our goal was isolation of extracellular particles to study their structures, penetration into cells, stability, intracellular distribution, and interferon (IFN) production. Extracellular nanomaterials were isolated from conditioned culture media of human embryonic and cancer cells by two-stage differential centrifugation. Cellular uptake of Cy5-labeled particles was evaluated using spectrofluorimetry and confocal fluorescent microscopy. IFN gene expression was analyzed by reverse transcription with real-time PCR and ELISA. Vesicles of 10–200 nm were isolated by centrifugation at 20,800× g at +4 °C for 30 min. The fluorescent vesicles were gradually accumulated inside cells for seven days. Intracellular distribution patterns of the Cy5-labeled vesicles differed from lysosomes stained with LysoRed tracker. IFNs α, β and γ were not detected after treatment with the vesicles. IFN λ was found in cells in the presence of allogenic but not autologous particles. The gradual cellular uptake occurred without significant differences between autologous and heterologous vesicles. Different localization of the extracellular vesicles (EV) and lysosomes along with weak innate immune response (if any) suggested membrane fusion. Full article

Single-cell RNA sequencing (scRNA-seq) has revolutionized genomic investigations by enabling the exploration of gene expression heterogeneity at the individual cell level. However, the complexity of scRNA-seq data analysis remains a challenge for many researchers. Here, we present OmniCellX, a browser-based tool designed to simplify and streamline scRNA-seq data analysis while addressing key challenges in accessibility, scalability, and usability. OmniCellX features a Docker-based installation, minimizing technical barriers and ensuring rapid deployment on local machines or clusters. Its dual-mode operation (analysis and visualization) integrates a comprehensive suite of analytical tools for tasks such as preprocessing, dimensionality reduction, clustering, differential expression, functional enrichment, cell–cell communication, and trajectory inference on raw data while enabling alternative interactive and publication-quality visualizations on pre-analyzed data. Supporting multiple input formats and leveraging the memory-efficient data structure for scalability, OmniCellX can efficiently handle datasets spanning millions of cells. The platform emphasizes user flexibility, offering adjustable parameters for real-time fine-tuning, alongside extensive documentation to guide users at even beginner levels. OmniCellX combines an intuitive interface with robust analytical power to perform single-cell data analysis and empower researchers to uncover biological insights with ease. Its scalability and versatility make it a valuable tool for advancing discoveries in cellular heterogeneity and biomedical research. Full article

Imaging of intracellular messengers, like calcium, is one of the most reliable methods to follow real-time changes in several aspects of cellular activity, like receptor activation. However, the analysis could be influenced and biased by several factors like the location, shape, and size of the regions of interest (ROIs) and by the detection and correction of the movement of the preparation. Programs which are provided by the manufacturers are expensive and cannot be shared by collaborators. Many self-made programs have been implemented lately which have in-built cell recognizer ROI identification functions. These programs focus on the soma of the cells and neglect the processes, because in full tissue preparation finding cells is still challenging. Subcellular imaging experiments are still rare. To the best of our knowledge there is no program which can automatically define ROIs for subcellular imaging experiments even in single indicated cells with complex morphology. We developed and validated a program to address this gap using simple and understandable mathematical methods for ROI determination and simple statistics for movement correction. Validation experiments were conducted on cochlear Deiters’ cells. Deiters’ cells have processed morphology which connects two fluid compartments in the cochlea. Because of the function and the fine morphology of the cell, it could be interesting to examine the subcellular Ca²⁺ handling mechanisms of it. Test impulses were activated by ATP. With some limitations the program successfully fulfilled its purpose. As a free, easily understandable, and open-source program, we hope it will help to analyze and plan subcellular experiments. Full article

Cell spheroids are widely studied for their potential applications in tissue engineering and regenerative medicine. The present work investigated the effects of cryopreservation on spheroids derived from ovine fibroblasts, depending on spheroid size (140 or 220 µm). Specifically, it explored how cryopreservation impacted several biological and physical parameters including cell damage, viability, metabolism, adhesion, proliferation, and spheroid mass density, weight, and diameter at three time points after thawing. A Live/Dead assay provided a visual assessment of cell damage, cell viability and metabolic activity were assessed by an Alamar Blue assay, and a replating assay evaluated cell adhesion and proliferation capabilities. Spheroid mass density, weight, and diameter were quantified by the W8 Biophysical Analyzer, creating accurate biophysical profiles. Real-time PCR (RT-PCR) analysis was employed to uncover gene expression changes following cryopreservation. Our findings indicate that spheroids measuring 140 µm in diameter largely maintained their biophysical features and cell viability post-cryopreservation, whereas those at 220 µm exhibited a decline in both vitality and mass density. The reduced vitality of 220 µm spheroids likely reflects size-related limitations in cryoprotectant diffusion and stress within the core. Overall, this study provides a comprehensive understanding of how cryopreservation affects ovine fibroblast spheroid biophysics and cellular integrity, laying the groundwork for improved preservation techniques for cell spheroids. Full article

Background: Cryopreservation of hematopoietic stem cells (HSCs) at −80 °C using uncontrolled-rate freezing is frequently employed in resource-constrained settings, yet concerns remain regarding long-term viability and clinical efficacy. Reliable post-thaw assessment is essential to ensure graft quality and engraftment success. Methods: This single-center, retrospective study evaluated 72 cryopreserved stem cell products from 25 patients stored at −80 °C for a median of 868 days. Viability was assessed using both acridine orange (AO) staining and 7-AAD (7-aminoactinomycin D) flow cytometry at three time points: collection (T0), pre-infusion (T1), and delayed post-thaw evaluation (T2). Associations between viability loss, storage duration, and clinical engraftment outcomes were analyzed. Results: Median post-thaw viability remained high (94.8%) despite a moderate time-dependent decline (~1.02% per 100 days; R² = 0.283, p < 0.001). Mean viability loss at T2 was 9.2% (AO) and 6.6% (flow cytometry). AO demonstrated greater sensitivity to delayed degradation, with a significant difference between methods (p < 0.001). Engraftment kinetics were preserved in most patients, with neutrophil and platelet recovery primarily influenced by disease type rather than product integrity. Notably, storage duration and donor age were not significantly associated with engraftment outcomes or CD34⁺ cell dose. Conclusions: Long-term cryopreservation at −80 °C maintains HSC viability sufficient for durable engraftment, despite gradual decline. While transplant outcomes are primarily dictated by disease biology and remission status, AO staining provides enhanced sensitivity for detecting delayed cellular damage. Notably, our viability-loss model offers a practical framework for predicting product quality, potentially supporting graft selection and clinical decision-making in real-world, resource-constrained transplant settings. Full article

Indoor positioning remains a recurrent and significant challenge in research. Unlike outdoor environments, where the Global Positioning System (GPS) provides reliable location information, indoor scenarios lack direct line-of-sight to satellites or cellular towers, rendering GPS inoperative and requiring alternative positioning techniques. Despite numerous approaches, indoor contexts with resource limitations, energy constraints, or physical restrictions continue to suffer from unreliable localization. Many existing methods employ a fixed number of reference anchors, which sets a hard balance between localization accuracy and energy consumption, forcing designers to choose between precise location data and battery life. As a response to this challenge, this paper proposes an energy-aware indoor positioning strategy based on Mobile Ad Hoc Networks (MANETs). The core principle is a self-adaptive control loop that continuously monitors the network’s positioning accuracy. Based on this real-time feedback, the system dynamically adjusts the number of active anchors, increasing them only when accuracy degrades and reducing them to save energy once stability is achieved. The method dynamically estimates relative coordinates by analyzing node encounters and contact durations, from which relative distances are inferred. Generalized Multidimensional Scaling (GMDS) is applied to construct a relative spatial map of the network, which is then transformed into absolute coordinates using reference nodes, known as anchors. The proposal is evaluated in a realistic simulated indoor MANET, assessing positioning accuracy, adaptation dynamics, anchor sensitivity, and energy usage. Results show that the adaptive mechanism achieves higher accuracy than fixed-anchor configurations in most cases, while significantly reducing the average number of required anchors and their associated energy footprint. This makes it suitable for infrastructure-poor, resource-constrained indoor environments where both accuracy and energy efficiency are critical. Full article

Background: Right heart failure (RHF) in dogs is marked by pathological fluid redistribution and extracellular fluid (ECF) accumulation, which intensifies cardiac work-load and disrupts systemic homeostasis. This study aimed to validate the clinical utility of phase angle (PhA), a key biomarker derived from bioelectrical impedance analysis (BIA), as a non-invasive and real-time indicator of fluid distribution abnormalities in canine RHF. PhA reflects cellular integrity and fluid balance, making it a promising tool for detecting ECF accumulation, one of the hallmark features of RHF. Additionally, the study assessed the feasibility and clinical applicability of the InBody M20 device in veterinary cardiology, supporting its potential role in monitoring and managing fluid-related complications in dogs with RHF. Methods: A total of 110 canine patients presenting to the Tokyo University of Agriculture and Technology Veterinary Hospital were enrolled and categorized into three groups: right-sided heart failure (RHF), left-sided heart failure (LHF), and healthy controls. Phase angle (PhA) was measured using the InBody M20 device, and plasma osmolality (OSM) was also assessed. Additionally, the effects of body weight and age on PhA values were analyzed to account for potential confounding factors. Results: Dogs in the RHF group exhibited significantly lower phase angle (PhA) values and higher plasma osmolality (OSM) compared to those in the LHF and control groups. A strong positive correlation was observed between PhA and OSM (r = 0.9211, p < 0.0001). Additionally, PhA measured at 5 kHz demonstrated a significant negative correlation with body weight (r = –0.4536, p = 0.0007), while PhA at 50 kHz showed a significant negative correlation with age (r = –0.3219, p = 0.0176). Conclusions: PhA is a reliable and non-invasive biomarker for assessing extracellular fluid accumulation and diagnosing right heart failure in dogs. Its strong correlation with plasma osmolality, as well as its associations with body weight and age, highlights its clinical relevance for comprehensive fluid status evaluation. The findings support the feasibility and applicability of using the InBody M20 device in veterinary cardiology to monitor and manage fluid-related complications in canine patients. Full article

In light of the growing significance of molecular biomarkers in central nervous system tumours, in this study, we aimed to comprehensively and quantitatively analyze the mRNA expression levels of DJ-1 (Parkinsonism-associated deglycase 7, PARK7), GDF15 (Growth Differentiation Factor 15), and MFGE8 (Milk Fat Globule-EGF Factor 8 Protein) in glioma and meningioma tissues and to thoroughly evaluate the associations between these gene expression profiles and clinicopathological parameters. Real-time PCR (qRT-PCR) analyses performed on tumour tissues obtained from a total of 27 glioma and 18 meningioma patients revealed that these three genes exhibited significantly elevated expression compared to control samples. Despite their different cellular origins, statistically significant positive correlations were observed between the expression levels of DJ-1, GDF15, and MFGE8 and both tumour grade and the Ki-67 proliferation index (Ki-67 Pi) in both glioma and meningioma cases, indicating that higher gene expression is associated with increased tumour aggressiveness in both tumour types. Receiver operating characteristic (ROC) curve analyses further confirmed the diagnostic and prognostic potential of these genes. Additionally, protein–protein interaction networks involving the target genes were characterised, providing valuable insights into their molecular mechanisms. These findings suggest that DJ-1, GDF15, and MFGE8 may play a role in the aggressiveness, invasion, and proliferation of gliomas and meningiomas. Moreover, integrating these genes as molecular biomarkers into tumour classification systems may provide a foundation for the development of personalised and targeted therapeutic strategies, although further studies are needed to support this. Full article

Plesiomonas shigelloides, a Gram-negative bacterium prevalent in aquatic environments and also frequently isolated from livestock and poultry, was investigated through integrated whole-genome sequencing and functional analyses. We deciphered the pathogenic mechanisms of P. shigelloides CA-HZ1, a highly virulent strain isolated from a novel piscine host, revealing a complete genome assembly with a 3.49 Mb circular chromosome and 311 kb plasmid housing 3247 predicted protein-encoding genes. Critical genomic features included 496 virulence factors and 225 antibiotic resistance genes. Pathogenicity analysis indicated that P. shigelloides was responsible for disease outbreaks. Antimicrobial susceptibility tests showed resistance to various drugs, such as kanamycin, erythromycin, and penicillin. Histopathological examination showed significant alterations in the infected hosts. Quantitative real-time PCR (qRT-PCR) was carried out to analyze immune-related gene (IL-6, IL-1β, IL-21, STAT1, and HSP70) levels in liver and intestinal tissues, demonstrating the potent immunity triggered by P. shigelloides infection. An analysis of the liver transcriptome revealed that P. shigelloides has the potential to influence the cellular composition, molecular functions, and biological processes. Collectively, this study describes the genomic basis underlying both the pathogenic potential and hypervirulence of P. shigelloides CA-HZ1, establishing a foundational framework for investigating its broad host tropism and immune response. Full article

The phosphoinositide 3-kinase (PI3K)/AKT signaling pathway is a crucial regulator of cellular metabolism, proliferation, and survival. It is frequently dysregulated in metabolic, cardiovascular, and neoplastic disorders. Despite the advancements in multi-omics technology, existing methods often fail to provide real-time, pathway-specific insights for precision medicine and drug repurposing. We offer Agentic RAG-Driven Multi-Omics Analysis (ARMOA), an autonomous, hypothesis-driven system that integrates retrieval-augmented generation (RAG), large language models (LLMs), and agentic AI to thoroughly analyze genomic, transcriptomic, proteomic, and metabolomic data. Through the use of graph neural networks (GNNs) to model complex interactions within the PI3K/AKT pathway, ARMOA enables the discovery of novel biomarkers, probable candidates for drug repurposing, and customized therapy responses to address the complexities of PI3K/AKT dysregulation in disease states. ARMOA dynamically gathers and synthesizes knowledge from multiple sources, including KEGG, TCGA, and DrugBank, to guarantee context-aware insights. Through adaptive reasoning, it gradually enhances predictions, achieving 91% accuracy in external testing and 92% accuracy in cross-validation. Case studies in breast cancer and type 2 diabetes demonstrate that ARMOA can identify synergistic drug combinations with high clinical relevance and predict therapeutic outcomes specific to each patient. The framework’s interpretability and scalability are greatly enhanced by its use of multi-omics data fusion and real-time hypothesis creation. ARMOA provides a cutting-edge example for precision medicine by integrating multi-omics data, clinical judgment, and AI agents. Its ability to provide valuable insights on its own makes it a powerful tool for advancing biomedical research and treatment development. Full article