Volume 5.
Issue 11.

Early detection is an important component of improving cancer diagnosis and treatment outcomes, yet conventional biomarker approaches often face limitations in sensitivity, specificity, and biological heterogeneity. The increasing availability of high-throughput genomic, transcriptomic, proteomic, metabolomic, and circulating biomarker data has created new opportunities for computational approaches to identify more informative diagnostic patterns. This review examines the application of artificial intelligence (AI) and machine learning (ML) to cancer biomarker discovery, with particular emphasis on laboratory-based approaches for early diagnosis. It discusses major biomarker classes, including circulating proteins, genomic and DNA alterations, microRNAs, metabolites, and liquid-biopsy markers, and examines how ML methods can support feature selection, dimensionality reduction, classification, and integration of molecular measurements. Applications across breast, lung, colorectal, pancreatic, ovarian, prostate, gastric, and liver cancers demonstrate how computational analysis can identify multi-biomarker signatures from complex biological datasets. The review also considers diagnostic performance measures, ROC analysis, validation strategies, overfitting, and the distinction between statistical discrimination and clinical utility. Challenges related to dataset heterogeneity, laboratory variability, external validation, interpretability, reproducibility, data privacy, and clinical implementation remain important barriers to translation. Future progress is likely to depend on integrating multiple molecular and clinical data types through multimodal and multi-omics AI approaches. Ultimately, the clinical value of AI-assisted biomarker discovery will depend on rigorous validation and successful translation of computationally identified signatures into reproducible, practical, and clinically useful laboratory tests.

This comprehensive analysis delves into the complex landscape of maternal and perinatal outcomes in the context of advanced maternal age, where pregnancy occurs beyond the conventional biological clock. The study explores a wide range of factors, including medical risks, social implications, and healthcare considerations associated with pregnancies in older mothers. It evaluates the impact of advanced maternal age on maternal health, fetal development, and perinatal outcomes, shedding light on the challenges and opportunities for addressing the evolving demographics of pregnancy. By navigating this terrain, we aim to contribute to informed healthcare decisions and policies that promote the well-being of both mothers and their infants.

This paper deals with the problem of determining the convex shape of the curb trajectory in order to ensure the stability of the curb, enhance the safety of overburden stripping and open pit mining. The method of cubic splines is used to determine the trajectory of the side. For application of this method the length of the pit base (or ledge) is divided into arbitrary n parts and in each partial segment the corresponding cubic spline function is constructed, being combined, each curve into a common curve, gives a common curve corresponding to the profile of the trajectory of the pit face.

The article describes the results of obtaining supramolecular complexes of albendazole with glycyrrhizic acid and monocalic salts in various molar ratios, studying their chemical structure by various physicochemical methods and studying the anthelmintic properties of the obtained supramolecular complexes.

In the modern world, much attention is paid to the development of information technologies in the XXI century. As the President of our country noted, the formation of a national informatization system and the mass introduction of modern information and communication technologies in all spheres of society requires future specialists to have special knowledge and skills in the field of computer technology. Therefore, algorithmization and programming is of particular importance in the formation of a national informatization system, especially for the prompt resolution of important military issues and their solutions. As already noted, the system of training, advanced training and retraining of military specialists in the field of programming is one of the main tasks today, as well as the development of local computer programs designed to solve military tasks, scheduling classes, automating the educational process as a whole and putting them into practice.

The general objective of this research paper is to rank the factors explaining the low level of non-tax revenue collection in order to identify the dominant factor. The present study is based on data collected by means of paper questionnaires in a survey of one hundred and twenty (120) individuals. Data processing was carried out using IBM SPSS Statistics 26 software. Two methods of analysis were adopted in this paper. These are descriptive analysis and econometric analysis. The descriptive analysis shows that the majority (55%) of the individuals surveyed affirm that Benin always records a low rate of non-tax revenue realization in relation to total budget revenue realization, and that the explanatory variables in our study are significantly related to the variable to be explained. The econometric results show that the most noteworthy factor contributing most to the low level of non-tax revenue collection is the low level of collection of contributions from state-owned companies, building rents and chancery duties, with a power of 0.7090 (R2 =0.7090). In second place we have non-application of the relevant laws and regulations, with a power of 0.3996 (R2 =0.3996), and in third place, irregular payment by taxpayers, with a power of 0.2182 (R2 =0.2182). To improve the collection of non-tax revenues - in this case, contributions from state-owned companies, building rents and chancellery fees - in line with sustainable development objectives, operational recommendations have been made based on the results of our analyses.

Today, the spread of toxic metals, which are considered anthropogenic pollution, causes a significant increase in environmental problems. Controlling the amount of heavy and toxic metals in the environment is an important ecological-analytical task.

This article discusses the problem of determining the analytical expression of the interconnectedness of such parameters as the movement of the face along the well z(t), the time t(z), the duration of the sublimation phenomenon and the propagation of a blast wave through the rock, as well as the pressure P in the detonation products in the well.

In the article, the amount of micro- and macro-elements in two types of glauconite produced during the industrial processing of licorice root from Beruni district of Karakalpakstan was studied based on the inductively coupled coil optical emission spectrometry method and compared with those in the literature. The obtained results were used to study the amount of macroelements K and R necessary for plants in the composition of soil and glauconite, and it was shown that it is possible to produce new types of organomineral fertilizers based on them. It has been shown that the processing of licorice root in our republic can solve the problems of disposal of industrial waste.

Based on the obtained results, the scientific basis of organomineral fertilizer production was developed based on the studied glauconite and wastewater and licorice root industrial waste.

Cotton is grown mainly for its fiber. Fiber is used for a very wide range of purposes. It differs from artificial fibers and provides a universal fiber because high-quality textile and technical products are produced from cotton fiber. According to the analysis, the created varieties should be resistant to changes that may be in agriculture in the next decade.