Search Results (118)

Melanogenesis is regulated by melanogenic enzymes such as tyrosinase (TYR), TRP-1, and TRP-2, whose expression is controlled by the microphthalmia-associated transcription factor (MITF). Various signaling pathways, including cAMP/PKA, MAPK/ERK, Wnt/β-catenin, and PI3K/Akt, are involved in this process and have been a focal point of research for treating pigmentation disorders. However, developing effective therapies for conditions like vitiligo remains a significant challenge. In this study, the effects of umckalin on melanogenesis and its molecular mechanisms were investigated using B16F10 cells, a mouse melanoma cell line widely used as a model for melanin production studies. B16F10 cells produce melanin via melanosomes and express key melanogenic enzymes such as TYR, TRP-1, and TRP-2, making them a reliable model system. Our findings demonstrate that umckalin promotes melanogenesis in a concentration-dependent manner by upregulating TRP-1 expression and activating the MITF signaling pathway. Additionally, umckalin modulated key signaling pathways, including GSK3β/β-catenin and MAPK, to enhance melanogenesis. In conclusion, umckalin enhances melanogenic enzyme activity by activating critical signaling pathways, thereby promoting melanin synthesis. These findings suggest that umckalin could be a promising candidate for developing therapeutic agents for pigmentation disorders such as vitiligo. Further studies are required to explore its mechanisms and clinical applications in greater detail. Full article

The role of oxidants and antioxidants in inflammatory bowel disease (IBD) has been actively explored since the early 1980s, starting with the role of the respiratory burst of neutrophils and ischemia in bowel pathology. Since that time, the enzymatic components contributing to the pool of reactive oxygen species, including superoxide, H₂O₂, and lipid hydroperoxides, and the counteracting antioxidants—catalase, glutathione peroxidases (Gpx), peroxiredoxins (PRDX), superoxide dismutases, and others—have been fleshed out. My perspective on IBD is from the role of the balance or imbalance of enzymatic oxidant sources and enzymatic antioxidants in the inflammatory process. I will present evidence on the involvement of oxidant and antioxidant processes in IBD based, as much as possible, on my experiences with Gpxs. This evidence will be discussed in terms of both the immune system and local bowel oxidant and antioxidant systems. As Gpxs are generally selenium-dependent, possible deficiencies in selenium uptake in active IBD and the impact on Gpx expression will be explored. The more recently introduced ferroptosis, an iron-dependent lipid peroxidation-based pathological process, will be reviewed for its possible involvement in IBD. Full article

Accurate primer and probe design is essential for molecular applications, including PCR, qPCR, and molecular multiparameter assays like microarrays. The novel software tool AssayBLAST addresses this need by simulating interactions between oligonucleotides and target sequences. AssayBLAST handles large sets of primer and probe sequences simultaneously and supports comprehensive assay designs by allowing users to identify off-target binding, calculate melting temperatures, and ensure strand specificity, a critical but often overlooked aspect. AssayBLAST performs two optimized BLAST-based searches for each primer or probe sequence, checking the forward and reverse strands for off-target interactions and strand-specific binding accuracy. The results are compiled into a mapping table containing binding sites, mismatches, and strand orientation, allowing users to validate large sets of oligonucleotides across predefined custom databases for a complete and optimal theoretical assay design. AssayBLAST was evaluated against experimental Staphylococcus aureus microarray data, achieving 97.5% accuracy in predicting probe–target hybridization outcomes. This high accuracy demonstrates the method’s effectiveness in reliably using BLAST hits and mismatch counts to predict microarray results. AssayBLAST provides a reliable, scalable solution for in silico primer and probe validation, effectively supporting large-scale assay designs and optimizations. Its accurate prediction of hybridization outcomes demonstrates its utility in enhancing the efficiency and reliability of molecular assays. Full article

This review summarizes recent findings on the diverse roles of bacterial sialidases in microbial biology. Bacterial sialidases, also known as neuraminidases, are exog α-lycosidases that cleave terminal sialic acid residues from a number of complex compounds designated as sialoglycoconjugates (glycoproteins, glycolipids and oligosaccharides). Metabolically, they are involved in sialic acid catabolism, providing energy, carbon and nitrogen sources. Catabolic degradation of sialic acids is a physiological feature that can be considered an important virulence factor in pathogenic microorganisms. Sialidases play a pivotal role in host–pathogen interactions and promotion of bacterial colonization. The activity of these enzymes enables bacterial adhesion, biofilm formation, tissue invasion, and also provides immune evasion by exposing cryptic receptors and modifying immune components. Many different perspectives are being developed for the potential application of sialidases. In the field of medicine, they are being explored as appropriate targets for antimicrobials, vaccines, diagnostic preparations and in tumor immunotherapy. In the field of enzymatic synthesis, they are used for the regioselective production of oligosaccharide analogs, enzymatic separation of isoenzymes and as a tool for structural analysis of sialylated glycans, among other applications. Full article

Hematologic malignancies, including leukemia, lymphoma, and multiple myeloma, pose significant therapeutic challenges due to their heterogeneity and high relapse rates. Nanotechnology has emerged as a promising avenue for precision drug delivery in these malignancies, allowing for enhanced drug concentration at tumor sites and reducing systemic toxicity. Recent developments in nanocarriers—such as liposomes, polymeric nanoparticles, and inorganic nanoparticles—have enabled targeted approaches, utilizing molecular markers specific to malignant cells to increase therapeutic efficacy while minimizing adverse effects. Evidence from preclinical and clinical studies underscores the potential of nanotechnology to improve patient outcomes by facilitating controlled release, improved bioavailability, and reduced toxicity. However, translating these advancements into clinical practice requires further research to validate their safety and efficacy. This review provides a comprehensive analysis of the latest innovations in nanotechnology for targeted drug delivery in hematologic malignancies, addressing current achievements and future directions for integrating these approaches into Clinical Hemato-Oncology. Full article

The nutritional value of Inga paterno seeds remains largely unexplored. Given the global protein deficiency, underutilized legumes like I. paterno could serve as alternative protein sources. This study evaluated the effect of sprouting on the composition, protein digestibility (PD) as soluble protein (SP), amino acid profile, free amino acids by UHPLC, and nutritional indicators of I. paterno seed flour. Seeds were sprouted for 0, 2, 4, 6, 8, or 10 days, then dried, milled, and analyzed. The seeds reached 100% sprouting after six days. Sprouting led to a 54.36% decrease in protein content but a 109% increase in the lipid fraction by day six. PD doubled after 8–10 days of sprouting. Additionally, total amino acid content significantly increased and the chemical score of majority essential amino acids tripled. After in vitro digestion, sprouted flour released higher amounts of free amino acids, particularly aspartic acid (from 9.10 ± 0.18 to 19.65 ± 0.97 mg/L), histidine (from 33.48 ± 0.61 to 46.29 ± 2.34 mg/L), alanine (from 16.32 ± 0.40 to 23.74 ± 0.07 mg/L), and lysine (from no detected to 7.12 ± 0.36 m/L). These findings suggest that sprouted I. paterno seeds could be a valuable, digestible protein source with enhanced nutritional quality, making them a promising ingredient for the food industry. Full article

Lung cancer is by far the leading cause of cancer death among both men and women, making up almost 25% of all cancer deaths Each year, more people die of lung cancer than colon, breast, and prostate cancer combined. The early detection of lung cancer is critical for improving patient outcomes, and automation through advanced image analysis techniques can significantly assist radiologists. This paper presents the development and evaluation of a computer-aided diagnostic system for lung cancer screening, focusing on pulmonary nodule segmentation in low-dose CT images, by employing HighRes3DNet. HighRes3DNet is a specialized 3D convolutional neural network (CNN) architecture based on ResNet principles which uses residual connections to efficiently learn complex spatial features from 3D volumetric data. To address the challenges of processing large CT volumes, an efficient patch-based extraction pipeline was developed. This method dynamically extracts 3D patches during training with a probabilistic approach, prioritizing patches likely to contain nodules while maintaining diversity. Data augmentation techniques, including random flips, affine transformations, elastic deformations, and swaps, were applied in the 3D space to enhance the robustness of the training process and mitigate overfitting. Using a public low-dose CT dataset, this approach achieved a Dice coefficient of 82.65% on the testing set for 3D nodule segmentation, demonstrating precise and reliable predictions. The findings highlight the potential of this system to enhance efficiency and accuracy in lung cancer screening, providing a valuable tool to support radiologists in clinical decision-making. Full article

The genus Quercus (Fagaceae) is one of the most widely distributed and species-diverse trees in the Northern Hemisphere. The present study addresses the investigation of the phyto-chemical profile by ten assays, the antioxidant activity scavenging of DPPH radicals, total phenolic content, total flavonoids, and antimicrobial activity against three pathogenic bacteria with the foliage of two species of red oak (Quercus sartorii and Quercus rysophylla). Both species of oak showed a high phenolic content in the aqueous extract (22,342.10 ± 3076.5 mg GAE/kg of plant and 17,747.14 ± 1139.9 mg GAE/kg of plant, respectively). In the flavonoid content, Q. sartorii showed a higher amount in the ethanolic extract (24,587.42 ± 996.3 mg QE/kg of plant), while for Q. rysophylla, it was methanolic extract (19,875.66 ± 2754.01 QE/kg of plant). In the DPPH radical scavenging activity, Q. sartorii showed the highest percentage of inhibition in the methanolic extract (81.14 ± 1.7%), while in Q. rysophylla, it was the ethanolic extract (82.60 ± 2.7%). In the antimicrobial tests, inhibition halos were obtained in the strains Acinetobacter baumannii and Staphylococcus aureus of both species. All this gives a guideline to comprehensively elucidate the metabolites present in these two species for further study and application in the dispute against pathogenic bacteria or in diseases related to the imbalance of reactive oxygen species (ROS). Full article

Cannabis sativa is used for multiple purposes, notably for its medicinal properties. It produces various secondary metabolites, including cannabinoids, terpenes, and flavonoids, which have therapeutic value and typically produce high amounts in female plants. The growth of the global cannabis market has led to intensive breeding efforts to develop elite cultivars with enhanced secondary metabolite profiles. As a dioecious and anemophilous plant, it produces staminate and pistillate inflorescences on separate plants and relies on wind for pollination, rendering traditional propagation methods challenging owing to high genetic recombination in progeny. Consequently, asexual propagation (micropropagation) is commonly employed to maintain female clones entirely. Micropropagation/direct organogenesis is a tissue culture technique that produces numerous disease-free clone plants in vitro more rapidly than traditional rooted cuttings. Factors such as sterilization, hormonal balance, explant type, nutrient additives, carbon source, pH, and environment influence the success of cultivar-specific micropropagation. In this review, we discussed how these factors affect cannabis micropropagation based on recent findings, emphasizing the importance of optimizing cultivar-specific protocols for long-term germplasm conservation and efficient breeding based on a mechanistic background. Full article

Accurate segmentation of Regions of Interest (ROI) in lung Computed Tomography (CT) is crucial for early lung cancer diagnosis and treatment planning. However, the variability in size, shape, and location of lung lesions, along with the complexity of 3D spatial relationships, poses significant challenges. In this work, we propose SALM (Segment Anything in Lung Model), a deep learning model for 2D and 3D ROI segmentation. SALM leverages Vision Transformers, proposing an adaptation of positional encoding functions to effectively capture spatial relationships in both 2D slices and 3D volumes using a single, unified model. Evaluation on the LUNA16 dataset demonstrated strong performance in both modalities. In 2D segmentation, SALM achieved a Dice score of 93% on 124,662 slices. For 3D segmentation using 174 3D images from the same dataset, SALM attained a Dice score of 81.88%. We also tested SALM on an external database (PleThora) on a subset of 255 pulmonary CT from diseased patients, where it achieved a Dice score of 78.82%. These results highlight SALM’s ability to accurately segment lung ROI in both 2D and 3D, demonstrating its potential to improve the accuracy and efficiency of computer-aided diagnosis for lung cancer. Full article

Fusobacterium necrophorum subspecies necrophorum, a resident of the rumen, is the causative agent of bovine liver abscesses. Currently, tylosin, a macrolide, is used in the feed to reduce liver abscesses. Because macrolides are medically important antibiotics, their use in food animal production is of public health concern. There is significant interest in finding antimicrobial alternatives. Bacteriophages that lyse subsp. necrophorum have the potential to replace tylosin. Our objective was to isolate bacteriophages lytic to subsp. necrophorum. Pooled ruminal fluid from slaughtered cattle and pooled sewage samples were collected and incubated overnight with lysine, and subsp. necrophorum strains and filtrates were spotted on F. necrophorum lawns. Phage plaques were harvested and purified. Bacteriophage isolation frequencies were compared between sample types, sampling dates, and necrophorum strains. Overall relative frequency of isolated bacteriophages lytic to subsp. necrophorum was 17.1%. The frequency of bacteriophage isolation ranged from 0 to 25.4% for ruminal fluid, and from 13.7 to 32.0% for sewage. Isolation frequency was significantly higher in sewage than in ruminal fluid samples (p < 0.01). Isolation rates varied significantly between necrophorum strains. Sewage was a rich source of bacteriophages lytic to necrophorum, which have the potential to be used to prevent liver abscesses. Full article

This research reviews deep learning methodologies for detecting leukemia, a critical cancer diagnosis and treatment aspect. Using a systematic mapping study (SMS) and systematic literature review (SLR), thirty articles published between 2019 and 2023 were analyzed to explore the advancements in deep learning techniques for leukemia diagnosis using blood smear images. The analysis reveals that state-of-the-art models, such as Convolutional Neural Networks (CNNs), transfer learning, Vision Transformers (ViTs), ensemble methods, and hybrid models, achieved excellent classification accuracies. Preprocessing methods, including normalization, edge enhancement, and data augmentation, significantly improved model performance. Despite these advancements, challenges such as dataset limitations, the lack of model interpretability, and ethical concerns regarding data privacy and bias remain critical barriers to widespread adoption. The review highlights the need for diverse, well-annotated datasets and the development of explainable AI models to enhance clinical trust and usability. Additionally, addressing regulatory and integration challenges is essential for the safe deployment of these technologies in healthcare. This review aims to guide researchers in overcoming these challenges and advancing deep learning applications to improve leukemia diagnostics and patient outcomes. Full article

Kidney cancer has become a major global health issue over time, showing how early detection can play a very important role in mediating the disease. Traditional histological image analysis is recognized as the clinical gold standard for diagnosis, although it is highly manual and labor-intensive. Due to this issue, many are interested in computer-aided diagnostic technologies to assist pathologists in their diagnostics. Specifically, deep learning (DL) has become a viable remedy in this field. Nonetheless, the capacity of existing DL models to extract comprehensive visual features for accurate classification is limited. Toward the end, this study proposes using ensemble models that combine the strengths of multiple transformers and deep learning model architectures. By leveraging the collective knowledge of these models, the ensemble enhances classification performance and enables more precise and effective kidney cancer detection. This study compares the performance of these suggested models to previous studies, all of which used the publicly accessible Dartmouth Kidney Cancer Histology Dataset. This study showed that the Vision Transformers, with an average accuracy of over 99%, were able to achieve high detection accuracy across all complete slide picture patches. In particular, the CAiT, DeiT, ViT, and Swin models outperformed ResNet. All things considered, the Vision Transformers consistently produced an average accuracy of 98.51% across all five-folds. These results demonstrated that Vision Transformers might perform well and successfully identify important features from smaller patches. Through utilizing histopathological images, our findings will assist pathologists in diagnosing kidney cancer, resulting in early detection and increased patient survival rates. Full article

Lactiplantibacillus plantarum is omnipresent in vegetable fermentations. Its large metabolic capacity and its ability to adapt to the fermenting microenvironment enable this species, in many cases, to dominate the microecosystem and drive the fermentation. In addition, its metabolic capacity enables it to produce bioactive compounds of great interest for human health. These attributes have directed research for many decades. The widespread application of next-generation sequencing approaches has enabled the genotypic verification of the phenotypically assessed attributes and supplemented them with novel insights, justifying the characterization of a multifunctional tool that has been awarded to this species. However, there are still issues that need to be properly addressed in order to improve our understanding of the microecosystem functionality and to enhance our knowledge regarding the capacities of this species. The aim of the present article is to collect and critically discuss the available information on Lp. plantarum subsistence in vegetable fermentations. Full article

Animal experiments have long been used as an educational tool in pharmacological education; however, from the perspective of animal welfare, it is necessary to decrease the number of animals used. ingAlthough using of simulators is effective, the development of these simulators is necessary when there is no existing simulator for animal experiments. In this review, we describe free, downloadable, and commercial simulators that are currently used in pharmacological education. Furthermore, we introduce two strategies to create simulators of animal experiments: (1) bioassay, and (2) experiments that measure the reaction time. We also describe five sigmoid curves (logistic curve, cumulative distribution function [CDF] of normal distribution, Gompertz curve, von Bertalanffy curve, and CDF of Weibull curve) to fit the results and their inverse functions. Using this strategy, it is possible to create a simulator that calculates the reaction time following drug administration. Moreover, we introduce a statistical model for local anesthetic agents using hierarchical Bayesian modeling. Considering the correlation among estimated parameters, we suggest it is possible to create simulators that give results more similar to those of animal experiments. The pharmacological education will be possible by these simulators at educational institutions where animal experiments are difficult due to various restrictions. It is expected that the number of simulator-based education programs will increase in the future. Full article