Throughout history, medicinal plants have been utilized, laying the foundation for contemporary medicine. Plant-derived compounds have been a vital source for developing medications. Colocasia esculenta stands out among traditional crops for its significant nutritional and medicinal potential, surpassing many other tuber crops. In this study, the antioxidant, mutagenicity, and antimutagenicity of four different extracts (hexane, acetone, methanol, and aqueous) of C. esculenta were investigated. Antioxidant activities of C. esculenta extracts were detected with the determination of total phenolic/flavonoid content (TPC/TFC), total antioxidant activity (TAC), and DPPH free radical scavenging activity. Acetone extract of C. esculenta exhibited the highest values in all TPC, TFC, TAC, and the DPPH free radical scavenging analyses. The mutagenic and antimutagenic activities of those four extracts were examined with TA98 and TA100 strains of Salmonella typhimurium. In higher concentrations, acetone and methanol extracts showed stronger mutagenic activity than the other extracts in both strains. The highest antimutagenic activity was observed in hexane and acetone in strain TA98.

Quantum computing (QC) is a computational science that provides efficient results for solving optimization problems. Quantum annealing (QA) is a form of QC and leverages superposition and quantum tunneling, which are phenomena of quantum mechanics. QA is used to solve real-life problems thanks to its superior properties. Therefore, studying QA with a specific focus on fantasy sports based on realistic scenarios offers a relatively under-explored, but promising approach, which represents the primary motivation of this study. Thus, this study presents a mathematical model for the Euroleague Fantasy Challenge (EFC) by Euroleague based on binary integer programming (BIP) to build the ideal team by selecting 10 players and one head coach among 288 players and 18 head coaches, in such a way that some team-building criteria set by the EFC are met and the PTM (Avg points) is maximized. To achieve it, this study uses the open-source Python library PyQUBO to express this model in the quadratic unconstrained binary optimization (QUBO) form and solves this model in the QUBO form through the D-Wave’s Leap Hybrid (quantum-classical) Solver to identify the ideal basketball team and head coach. Accordingly, a mathematical model based on BIP is presented to find the team formation with the highest PTM (Avg points) value, considering various potential team formations for the chosen team. It then converts this model into the QUBO form in the PyQUBO library and solves it on both the D-Wave’s Advantage 4.1 and Hybrid Solver. Both solvers suggest the same line-up (1 guard, 3 forwards, 1 center) as the ideal line-up. This study will hopefully contribute to the relevant field by encouraging further studies to leverage QC to guide complex decision-making processes in all team sports.

Glycans, a key component of cells, are abundant and diverse biopolymers found in covalent bonds of sucrose attached to proteins and lipids. They significantly contribute to mass and structural variation in biological systems. In order to characterize glycans, study their effects in various experiments, and comprehend their roles, it is necessary to isolate them from the proteins with which they are associated. Chemical methods and various enzymes separate glycans. The ease of application of chemical methods, despite their low cost, chemical methods ease of application affects the chemical structure of both glycans and the remaining part of the polypeptide during deglycosylation. Additionally, the high salt content of the separated glycans makes mass spectrometry analysis of these glycants difficult. For these reasons, the use of enzymes in glycan studies has increased in recent years. One of the most commonly used enzymes in this field, N-glycosidase F has a wide spectrum and the ability to successfully release various N-glycan structures from glycoprotein.

In this study, the PNGase F enzyme, secreted by Flavobacterium meningosepticum, was efficiently produced in a recombinant manner. The enzyme, which contains 314 amino acids, is the most effective method for removing N-glycan from glycoproteins.

Microgreens are plants consumed before reaching maturity. Vegetable seeds are generally used in their production. Microgreens are used in salads and various dishes in terms of their aromatic aspects. It is known that microgreens are an important source of antioxidants. Although microgreens are easy and fast to produce, producers’ lack of knowledge limits the production of microgreens. Seed spacing has also been not correctly verified in previous studies, as well. Within the scope of the study, okra (Abelmoschus esculentus L. cv. ‘Sultani’), carrot (Daucus carota L. cv. ‘Nantes’), leek (Allium porrum L. cv. ‘Hotanlı’), spinach (Spinacia oleracea L. cv. ‘Matador’), cress (Lepidium sativum L. cv. ‘Tere’) vegetables were sown at two different sowing densities (the average amount of seeds that can fit on a 1 cm² surface area-dense sowing and 1/3 of this amount-sparse sowing). Plant weight, yield, width of root collar, plant height, water soluble dry matter, ascorbic acid were evaluated. Results indicated that ocra microgreens’weight was higher than the other microgreens’ and had higher values in terms of yield. Ocra microgreens also demonstrated the highest total soluble solids value. The yield of okra, spinach and cress microgreens increased with dense planting. However, it was found that the increase in planting density and the increase in yield were not at the same rate. Cress microgreens had the highest value in terms of ascorbic acid value.

Ensuring the security of digital communication and data transfer has become essential in the modern era. Classical cryptographic techniques are increasingly vulnerable due to advances in quantum technologies and algorithms. Consequently, quantum computers and quantum communication offer promising solutions for secure data transfer and encryption. This study explores the generation of Quantum Digital Signatures (QDS) using Quantum Continuous Variables (QCV), providing a novel approach to secure digital signature technologies.

The paper outlines the core principles of QDS generation with QCV, detailing the signature creation and verification processes. It highlights the advantages of this technology in secure communication and data transfer and discusses potential security vulnerabilities and future development prospects. Quantum Continuous Variables (QCVs), typically used in quantum optical systems, represent physical quantities with continuous spectra, such as the wavelength or phase of light. These variables enable efficient and secure quantum information processing and communication.

Despite significant progress in quantum cryptography protocols using QCVs, practical application and optimization of these technologies face numerous challenges. These include complexities in preparing and measuring quantum states, managing quantum errors, and achieving higher efficiency and security standards. Moreover, the practical applications of QCV in industrial contexts remain limited, highlighting the need for further experimental and applied research.

The methodology for generating QDS using QCVs involves employing specific quantum states, such as coherent and squeezed states. The process includes key distribution, signature creation and verification, and addressing potential quantum attacks. The system model comprises a sender (Alice), a receiver (Bob), and an arbiter (Charlie), facilitating secure and authenticated message transmission.