Chemija

Title

2025-10-14T09:56:02+03:00

2025-10-14T09:57:59+03:00

The inspiring scientific career of Valdemaras Razumas

2025-10-14T10:10:19+03:00

Beyond potentiometry: an amperometric approach to urea detection using antimony electrodes

2025-10-14T11:15:39+03:00

In this study, we present an amperometric urea biosensor based on a custom-made antimony electrode modified with an enzymatic membrane containing immobilised urease. The biosensor showed a high sensitivity, ranging from 306.6 to 77.5 nA/mM depending on the buffer solution capacity (5–50 mM PBS). Stability tests demonstrated that the sensor retained 65% of its initial activity after 10 days at room temperature. Good repeatability was observed, with relative standard deviations below 10% for 10 replicate measurements at 0.5 mM urea. Validation with aqueous samples showed a strong correlation with a commercial colorimetric assay, with deviations not exceeding 10%. During the tests with biological samples (human saliva and serum), the biosensor reported lower urea concentrations compared with the colorimetric method, indicating that interfering compounds present in complex biological matrices can affect biosensor performance. The developed biosensor represents a simple, cost-effective and adaptable platform for urea determination, showing a strong potential for integration into point-of-care diagnostic systems.

Elemental composition and bioactivity of morphological parts extracts of winter savory (Satureja montana L.)

2025-10-14T11:49:14+03:00

Winter savory (Satureja montana L.) is well known to exhibit strong antioxidant and antibacterial properties. Winter savory is rarely found growing wild in Lithuania; however, as a common garden plant, it has been the subject of only a few studies. The goal of this research was to determine the mineral composition of winter savory and evaluate how well seven different solvents compositions – deionised water, 50% methanol (MeOH), 75% MeOH, 50% ethanol (EtOH), 75% EtOH, 2% sodium dodecyl sulfate (SDS) and 2% Triton X-100 – could extract phytochemicals. The results showed that the elemental composition was dominated by calcium (from 4231.23 ± 546.48 mg kg^–1 in stems to 11494.27 ± 785.01 mg kg^–1 in leaves) and potassium (from 3626.69 ± 427.98 mg kg^–1 to 6321.68 ± 241.53 mg kg^–1, respectively). It was also determined that the total concentration of phenolic compounds in the plant extracts varied depending on the solvent and morphological part used. Concentrations ranged from 23.91 mg g^–1 in the stems when ethanol was used to 138.96 mg g^–1 in the leaves when methanol was used. Additionally, phenolic acids ranged from 6.45 mg g–1 in the aqueous extract of flowers to 92.82 mg g^–1 in the leaf extract obtained with the surfactant Triton X-100. Flavonoid content varied from 9.94 mg g^–1 in flower extracts obtained with distilled water to 151.39 mg g^–1 in leaf extracts when the surfactant SDS was used. Winter savory extracts exhibited a high radical scavenging activity by DPPH assays ranging from 13.01 to 85.71%. The strongest antibacterial effect was observed in 2% SDS stem extract against Bacillus subtilis. Considering all the analysis performed, we can conclude that SDS is the most effective solvent for winter savory.

The effect of folates on the oxidation reaction of methyl linoleate in micellar solutions

2025-10-14T11:15:15+03:00

The antiradical/antioxidant properties of folic acid (FA) and its conformational derivatives – 7,8-dihydrofolate (DHF), 5,6,7,8-tetrahydrofolate (THF) and 5-formyl-5,6,7,8-tetrahydrofolate (5-FTHF) – were studied at the physiological temperature and pH in the micellar aqueous system of the model reaction of methyl linoleate peroxidation with molecular oxygen. It was established that folates exhibit antioxidant properties, thereby inhibiting the peroxidation of methyl linoleate.
Quantitative kinetic studies of selected folates revealed the comparative growing order of the antiradical/antioxidant reactivities: FA < 5-FTHF < THF ≅ DHF.
Investigation of the antioxidant properties of folates is urgent for understanding their role in the prevention of pathologies in the body. They may have potential in treating numerous pathological conditions in which oxidative stress is a clinically important component.

Recent advances in biomolecular analysis by ultraviolet surface-enhanced resonance Raman spectroscopy: A review

2025-10-14T11:15:02+03:00

Ultraviolet surface-enhanced resonance Raman spectroscopy (UV-SERRS) offers the ultrasensitive, reliable and selective analysis and sensing of biomolecules due to the combination of surface-enhancement and resonance enhancement of the Raman signal of studied molecules. In this Review, we provide the background of the technique and discuss the challenges related to ultraviolet plasmonics as well as the ability to employ the non-plasmonic substrates. We also highlight the recent applications of UV-SERRS in analysis of biomolecules. Finally, the advantages and future directions of the method are provided.

A minireview on oxygen-insensitive nitroreductases: reaction mechanisms and their biomedical impact

2025-10-14T13:10:52+03:00

In this paper, we try to summarise some historically identified structural and catalytic properties of an important super-family of flavoenzymes, the oxygen-insensitive bacterial nitroreductases (NRs). We also review how these mechanistic properties have underpinned diverse roles in medicine and biomedical research, with an emphasis on the last decade. NRs perform the NAD(P)H-dependent two/four-electron reduction of nitroaromatic compounds (ArNO₂) and the two-electron reduction of quinones (Q) without the formation of free radicals of these compounds. This has significant implications for their behaviour in living systems. We reviewed the structural, catalytic and potentiometric properties of NRs and their oxidant substrate specificity, as well as the structural factors influencing it. Biomedical aspects of the function and application of NRs were also reviewed, including the importance of NRs in antibiotic resistance, their applications in cancer gene therapy, and NR-mediated cellular ablation technologies.

Effect of graphite particle size on the physicochemical properties and dopamine-sensing performance of reduced graphene oxide

2025-10-14T11:19:49+03:00

Graphene oxide (GO) was synthesised from graphite powders of two different particle sizes (≤50 and ≥149–≤840 μm) using the Hummers’ method and subsequently reduced by thermal shock at 800°C to obtain reduced graphene oxide (rGO). The obtained samples, denoted rGO_1 (from smaller graphite particles) and rGO_2 (from larger graphite flakes), were investigated to evaluate the influence of precursor size on their physicochemical properties and electrochemical performance. Structural characterisation was carried out by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and nitrogen adsorption–desorption analysis. The results confirmed the removal of oxygen-containing groups after thermal reduction and indicated differences in crystallite domains and defect density depending on the size of the graphite precursor. Electrochemical measurements demonstrated that both samples were able to detect dopamine (DA). The electrodes showed linear DA detection in a concentration range of 1–19.96 μM, with detection limits of 61.55 nM for rGO_1 and 98.17 nM for rGO_2. Sensitivities were determined as 6.44 and 12.20 μA μM–1 cm–2, respectively. Our results suggest that the properties of rGO can be tailored by controlling the size of the graphite precursor, which may provide new opportunities for the design of rGO-based electrochemical sensors.

New derivatives bearing alkyl phosphonic acid moieties as a promising scaffold against drug-resistant H69AR small cell lung cancer models

2025-10-14T13:15:13+03:00

Small cell lung cancer (SCLC), although less common than non-small cell lung cancer (NSCLC), is an aggressive and lethal form of lung cancer. Even if it was diagnosed and started being treated early, it still contributes to poor survival rates. Standard therapies, including platinum-based chemotherapy and immune checkpoint inhibitors, offer limited and short-lived benefits due to the rapid disease relapse and widespread metastasis. One of the promising strategies for the new drug against SCLC development is the rational design of 9H-carbazole or other structurally similar chromophores with an alkyl phosphonic acid moiety, expecting dual-targeting ability, potentially targeting both nuclear and cytoplasmic effectors involved in SCLC progression and resistance. The aim of this work was to synthesise phenothiazine, phenoxazine, anthraquinone and substituted carbazole derivatives, containing an alkyl phosphonic acid moiety and to evaluate their in vitro antiproliferative activity using the well-established anthracycline-resistant H69AR small cell lung cancer (SCLC) cell model. The results demonstrate that 9H-carbazole derivatives bearing alkyl phosphonic acid groups could be explored as a promising scaffold class for the further development of compounds against drug-resistant SCLC.

The use of physics-informed neural networks (PINNs) to map the Zn2+ nanoparticles diffusion in Swiss chard: an AI simplified modelling approach

2025-10-14T13:11:55+03:00

Electrochemical processes are central to energy storage, catalysis, corrosion and sensing, yet understanding and optimising these systems remains challenging. Physics-informed neural networks (PINNs) offer a promising approach by integrating physical laws into machine learning models for improved interpretability and accuracy. In this work, we develop a PINN to simulate the diffusion and electric-field-driven transport of Zn²⁺ ions released from ZnO nanoparticles in the beetroot – Swiss chard – leaf tissue. The model embeds the Poisson’s equation for electric potential and the Nernst–Planck equation for ion flux into the network’s loss function, enabling it to learn physically consistent potential and concentration fields with minimal data. The PINN predictions reveal that Zn²⁺ ions accumulate near leaf edges, a phenomenon also observed experimentally. Using the trained model, we evaluate microelectrode sensor array designs and find that a hexagonal electrode layout would capture the edge-concentrated Zn²⁺ distribution more effectively than a uniform grid. This case study demonstrates how AI modelling informed by physics can accurately replicate experimental trends and guide the design of better electrochemical sensors. The results highlight the broader potential of PINNs to advance electrochemical research by combining data-driven learning with established physical electrochemical principles.