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A novel voltammetric sensor was constructed by modifying a glassy carbon electrode with a composite material consisting of platinum–nickel-doped tin oxide and carbon black (PtNiSnO2-CB/GCE), enabling highly sensitive differential pulse voltammetry (DPV) determination of trazodone HCl (TRZ). The DPV experimental parameters, including the composition of the supporting electrolyte and instrumental settings, were carefully optimized to achieve maximum analytical efficiency. Within the linear range of 1–10 µM, quantification of TRZ molecules could be performed without the preconcentration step. When applying a 60 s accumulation time (in the range 0.02–0.2 µM of TRZ), the detection limit reached 4.1 nM (1.67 mg L−1), indicating superior sensitivity compared to previously reported voltammetric techniques. The method demonstrated good reproducibility, with a relative standard deviation of 4.3% for 10 repeated measurements at 0.06 µM TRZ. The developed sensor exhibits excellent stability, simplicity of fabrication, and operational convenience. Its practical applicability was confirmed by the successful analysis of molecules of TRZ in diverse sample types, including pharmaceutical products, urine, plasma, river water, and artificial gastric and intestinal fluids, with recovery rates between 97.7% and 104.2%. Flow injection analysis (FIA) with amperometric detection was also performed for TRZ molecule determination.

Currently, endometrial carcinoma (EC) is the most common genital cancer in high-income countries. Some types of endometrial hyperplasia (EH) may be progressing to this malignancy. The diagnosis of EC and EH is based on time consuming histopathology evaluation, which is subjective and causes discrepancies in reassessment. Therefore, there is a need to create methods of objective evaluation allowing the diagnosis of early changes. The study aimed to simultaneously asses Fourier Transform Infrared (FTIR) and Raman spectroscopy combined with multidimensional analysis to identify the tissues of endometrial cancer, atypical hyperplasia and the normal control group, and differentiate them. The results of FTIR and Raman spectroscopy revealed quantitative and qualitative changes in the nucleic acid and protein in the groups of cancer and atypical hyperplasia, in comparison with the control group. Changes in the lipid region were also observed in Raman spectra. Pearson correlation coefficient demonstrated a statistically significant correlation between Raman spectra for the cancer and atypical hyperplasia groups (0.747, p < 0.05) and for atypical hyperplasia and the controls (0.507, p < 0.05), while FTIR spectra demonstrated a statistically significant positive correlation for the same group as in Raman data and for the control and cancer groups (0.966, p < 0.05). To summarize, the method of spectroscopy enables differentiation of atypical hyperplasia and endometrial cancer tissues from the physiological endometrial tissue.

A novel voltammetric sensor was constructed by modifying a glassy carbon electrode with a composite material consisting of platinum–nickel-doped tin oxide and carbon black (PtNiSnO[sub.2]-CB/GCE), enabling highly sensitive differential pulse voltammetry (DPV) determination of trazodone HCl (TRZ). The DPV experimental parameters, including the composition of the supporting electrolyte and instrumental settings, were carefully optimized to achieve maximum analytical efficiency. Within the linear range of 1–10 µM, quantification of TRZ molecules could be performed without the preconcentration step. When applying a 60 s accumulation time (in the range 0.02–0.2 µM of TRZ), the detection limit reached 4.1 nM (1.67 mg L[sup.−1]), indicating superior sensitivity compared to previously reported voltammetric techniques. The method demonstrated good reproducibility, with a relative standard deviation of 4.3% for 10 repeated measurements at 0.06 µM TRZ. The developed sensor exhibits excellent stability, simplicity of fabrication, and operational convenience. Its practical applicability was confirmed by the successful analysis of molecules of TRZ in diverse sample types, including pharmaceutical products, urine, plasma, river water, and artificial gastric and intestinal fluids, with recovery rates between 97.7% and 104.2%. Flow injection analysis (FIA) with amperometric detection was also performed for TRZ molecule determination.

A novel voltammetric sensor was constructed by modifying a glassy carbon electrode with a composite material consisting of platinum-nickel-doped tin oxide and carbon black (PtNiSnO -CB/GCE), enabling highly sensitive differential pulse voltammetry (DPV) determination of trazodone HCl (TRZ). The DPV experimental parameters, including the composition of the supporting electrolyte and instrumental settings, were carefully optimized to achieve maximum analytical efficiency. Within the linear range of 1-10 µM, quantification of TRZ molecules could be performed without the preconcentration step. When applying a 60 s accumulation time (in the range 0.02-0.2 µM of TRZ), the detection limit reached 4.1 nM (1.67 mg L ), indicating superior sensitivity compared to previously reported voltammetric techniques. The method demonstrated good reproducibility, with a relative standard deviation of 4.3% for 10 repeated measurements at 0.06 µM TRZ. The developed sensor exhibits excellent stability, simplicity of fabrication, and operational convenience. Its practical applicability was confirmed by the successful analysis of molecules of TRZ in diverse sample types, including pharmaceutical products, urine, plasma, river water, and artificial gastric and intestinal fluids, with recovery rates between 97.7% and 104.2%. Flow injection analysis (FIA) with amperometric detection was also performed for TRZ molecule determination.

The paper presents experimental studies of dielectric properties of nanofluids based on ethylene glycol and SC-TiO 2 nanoparticles with average size of 15–40 nm with various mass concentrations. The dielectric permittivity both real part and imaginary part as a function of temperature and frequency were measured. Also, dependence ac conductivity on frequency, temperature, and mass concentration were investigated. Based on the curves of ac conductivity, dc conductivity was calculated, and 400 % enhancement in dc conductivity was exposed.

The paper presents experimental studies of dielectric properties of nanofluids based on ethylene glycol and SC-TiO sub(2) nanoparticles with average size of 15-40 nm with various mass concentrations. The dielectric permittivity both real part and imaginary part as a function of temperature and frequency were measured. Also, dependence ac conductivity on frequency, temperature, and mass concentration were investigated. Based on the curves of ac conductivity, dc conductivity was calculated, and 400 % enhancement in dc conductivity was exposed.

The paper presents experimental studies of dielectric properties of nanofluids based on ethylene glycol and SC-TiO2 nanoparticles with average size of 15-40 nm with various mass concentrations. The dielectric permittivity both real part and imaginary part as a function of temperature and frequency were measured. Also, dependence ac conductivity on frequency, temperature, and mass concentration were investigated. Based on the curves of ac conductivity, dc conductivity was calculated, and 400 % enhancement in dc conductivity was exposed.

Diabetic retinopathy (DR) is a growing health problem worldwide and is a leading cause of visual impairment and blindness, especially among working people aged 20-65. Its incidence is increasing along with the number of diabetes cases, and it is more common in developed countries than in developing countries. Recent research in the field of diabetic retinopathy diagnosis is using advanced technologies, such as analysis of images obtained by ophthalmoscopy. Automatic methods for analyzing eye images based on neural networks, deep learning and image analysis algorithms can improve the efficiency of diagnosis. This paper describes an automatic DR diagnosis method that includes processing and analysis of ophthalmoscopic images of the eye. It uses morphological algorithms to identify the optic disc and lesions characteristic of DR, such as microaneurysms, hemorrhages and exudates. Automated DR diagnosis has the potential to improve the efficiency of early detection of this disease and contribute to reducing the number of cases of diabetes-related visual impairment. The final step was to create an application with a graphical user interface that allowed retinal images taken at cooperating ophthalmology offices to be uploaded to the server. These images were then analyzed using a developed algorithm to make a diagnosis.