Modern Research Research Articles

Testing influence of Hubble tension on the early Universe

The Hubble tension has profoundly shaped modern cosmological research. This study explores its impact on the early-universe physics in the modified emergent dark energy (MEDE) and ΛCDM model using Planck PR4, BK18, DESI2024/2025, and supernova samples (Pan+, Union3). First, Hubble constant negligibly affects the tensor-to-scalar ratio (r<0.031 at 95%C.L.). Inclusion of DESI2025 achieves a 46% uncertainty reduction in key parameters. For CMB power spectra, DESI systematically amplifies TT/BB spectral discrepancies. Second, electron ionization fractions Xe(z) display pronounced deviations from the ΛCDM model at z=9.17, suggesting a connection between Hubble tension and reionization history. This finding resonates with JWST measurements on high-redshift galaxy evolution. Future observations, such as 21-cm surveys, are highly anticipated to resolve these tensions by probing early-universe evolution and dark energy interactions.

Science literacy levels of plant metabolism learning for biology education students

Scientific literacy is a person's ability to think and behave scientifically, apply scientific knowledge, and make decisions in solving problems in everyday life. Biology students are expected to be able to develop scientific literacy. One of them is in the material of plant metabolism. Understanding the concept of plant metabolism will help students in implementing the concept of biological science in everyday life. This is because biology is a branch of natural science that has the potential and makes a major contribution to solving global problems, such as food, health, social, energy, economic, environmental, and technology. This study aims to see the level of science literacy of biology students on plant metabolism material, which is one of the basic materials for modern biology learning and research in the 21st century. This type of research is descriptive quantitative with a survey method, with respondents of undergraduate students of the Ahmad Dahlan University Biology Education Study Program. The test instruments used were the Scientific Inquiry Literacy Test (SILT) and the Multidimensional Scientific Literacy Test (MSLT). Science Literacy (SL) questions have seven indicators. The question material used in the test instrument is knowledge of photosynthesis, cellular respiration, phytochemical biosynthesis pathways, and implementation of plant metabolism concepts in the fields of health and pharmacology. The findings result showed a significant increase in the seven levels of scientific literacy indicators, where the average post-test score was always higher than the pre-test. Most students were included in the conceptual group. The conclusion of the study was that the fairly high scientific literacy scores at the seven levels indicate that students have understood and internalized the concepts and contents of plant metabolism materials, are able to read, interpret, and analyze data, and know the role and application of plant metabolism processes in the development of the world of health and pharmacology, so it can be said that during the learning process there has been an increase in the science literacy of biology students.

ADVANCES IN HOST-PATHOGEN INTERACTION MECHANISMS IN EMERGING INFECTIOUS DISEASES-A Narrative ReviewADVANCES IN HOST-PATHOGEN INTERACTION MECHANISMS IN EMERGING INFECTIOUS DISEASES-A Narrative Review

Background: Emerging infectious diseases (EIDs) present a growing global health threat, often fueled by complex and dynamic interactions between hosts and pathogens. Understanding these interactions at molecular, cellular, and ecological levels is critical for improving clinical outcomes, enhancing surveillance, and informing therapeutic strategies. Given the rising frequency of zoonotic spillovers and pathogen evolution, an updated synthesis of host-pathogen interaction mechanisms is essential for modern infectious disease research and practice. Objective: This narrative review aims to explore recent advancements in the understanding of host-pathogen interactions, with a focus on mechanisms that underpin disease emergence, immune modulation, and cross-species transmission. Main Discussion Points: The review discusses major themes including receptor-mediated pathogen entry, immune evasion strategies, host genetic and epigenetic factors, ecological influences on transmission, and the role of high-throughput omics and computational modeling in advancing the field. Variability in host responses, the impact of community structure, and the limitations of current study designs are also critically examined. Conclusion: While the body of evidence provides valuable insights into host-pathogen interactions, it remains limited by methodological heterogeneity and underrepresentation of diverse populations. Future research should prioritize longitudinal, integrative, and mechanistically focused approaches to better translate molecular insights into clinical and public health applications.

Novel methods to quantify gait rehabilitation following ankle-foot fractures.

Lower limb fragility fractures included a break in bone from the pelvis to the foot. Weight-bearing and walking stability stand as key performance indicators to quantify fracture restoration. Normally, progress in fracture rehabilitation is observed through clinical assessments and patients' responses, and modern research also presents instrumented gait analysis. There exists a gap to statistically compute the regaining in patients' weight-bearing ability and walking stability following fractures. This study introduces methods to advance the analysis of instrumented signals and evaluate walking stability in fracture-healing patients. The centre of pressure (CoP) signals were captured for four conditions: tibia/fibula/talus fracture near the ankle (AF), lower-leg shaft fracture (LF), calcaneus fractures (CF), and normal ankle (NA). The time derivative for CoP signals showed impulsive responses during the loading and unloading transitions which were then modelled and transformed to the frequency domain. The developed models were further analysed by applying Nyquist and Bode methods and margins of stability were calculated for the fractured and healthy subjects. Results showed a substantial decline (Kruskal-Wallis's test, p < 0.001) in the intralimb stability of all three fractures. Also, there was a strong interlimb dependency (p < 0.001) observed between fractured and intact limbs applying Spearman's correlation during double limb support periods. Overall, the calcaneus fracture (CF) exhibited minimum intralimb stability and increased interlimb dependency. These methods stand clinically important in monitoring patients' rehabilitation and in decision-making about alternative treatment plans.

Recent Advances in Machine Learning‐Assisted Design and Development of Polymer Materials

ABSTRACTThe traditional research paradigm for polymer materials relies heavily on time‐consuming and inefficient trial‐and‐error methods, which are no longer sufficient to meet the demands of modern research and development. With the rapid advancement of big data and artificial intelligence technologies, machine learning has emerged as a powerful data analysis tool, revolutionizing polymer material research and development. This paper provides an overview of machine learning techniques, summarizes common machine learning algorithms, and reviews recent progress in machine learning‐assisted polymer material design and development. Key areas include polymer sequence design, material property prediction, classification and identification, and applications leveraging computer vision technologies. Furthermore, this study discusses several critical challenges currently faced by the field and offers perspectives on future directions .

Thermal‐Spin Conversion: Mechanism, Materials, and Determinants of the Spin Seebeck Effect

This study provides an in‐depth review of a major aspect of the broader field of spin caloritronics, focusing specifically on the spin Seebeck effect (SSE). To better frame the discussion, this study starts by outlining the key concepts of pure spin‐driven current creation, manipulation, and detection, which are crucial for interpreting the underlying principles of the effect. Utilizing this framework, it proceeds to a detailed exploration of the SSE, which describes the creation of spin Seebeck voltage (SSV) induced by a temperature gradient in magnetic materials, resulting in the transfer of the generated spin current into an adjacent normal metal. Following this, this study discusses the spin Seebeck coefficient, which indicates how effectively a material can convert a temperature gradient into SSV. Several factors impact the magnitude of this coefficient, including temperature gradient, magnetic field, interface quality, a broad spectrum of materials for producing and detecting SSV, magnetic properties, etc. In conclusion, this study addresses resolved and persisting challenges while exploring SSE's future in waste heat recovery for advanced energy‐saving technologies. This study offers a comprehensive assessment of SSE, covering its theory, advancements, and pivotal role in modern spintronics, benefiting both newcomers and researchers.

Application of Chinese Medicine Poria cocos in Anti-tumor

Poria cocos is a type of traditional Chinese medicine which has rich pharmacological effects, including anti-tumor, liver protection, diuretic, anti-aging, anti-inflammatory, lowering blood lipids, and enhancing immunity. The chemical components of Poria Cocos mainly include polysaccharides, triterpenes, fatty acids, sterols and enzymes, among which Poria Cocos and triterpenes play an important role in antitumor, liver protection and antiaging. Modern research shows that poria can improve the therapeutic effect of chemotherapy drugs in cancer, reduce the negative effects of chemoradiotherapy and prevent the proliferation of cancer cells. Triterpenoid components, such as caroicimaric acid, can inhibit tumor cell proliferation by regulating the cycle and promoting tumor cell apoptosis. As a traditional Chinese medicine, poria has great potential in antitumor applications.

Tailored Cation Distribution in High-Entropy Mn-Co-Ni-Cu-Zn Oxides: Toward Advanced OER Electrocatalysis.

Water splitting is a highly promising technology for renewable energy and energy storage. The primary challenge is to develop cost-effective, improved, long-lasting, and highly efficient electrocatalysts for the oxygen evolution reaction (OER). High-entropy oxides (HEOs) are the next generation of nanomaterials due to their complexity and significant role in modern scientific research. In this work, a layered structured (MnCoNiCuZn)O HEO is prepared using a simple metal-organic framework (MOF)-assisted strategy, and the effect of increasing cation concentration on the performance of the OER is evaluated. The chemical bonding interaction of this structure was revealed by XPS and EDS mapping techniques, demonstrating favorable electronic conductivity for optimizing the OER performance in the alkaline medium. Among the different cation variations, the HEO with an equal concentration of cations exhibits the lowest overpotential of 319 ± 5 mV @ 50 mA cm-2, accompanied by a Tafel slope of 78 ± 7 mV dec-1. Even at higher current densities, the HEO material exhibits the lowest overpotential, as evidenced by the Tafel values. This study suggested a design for HEO-based electrocatalysts, which achieves admirable water-splitting efficiency for sustainable hydrogen and oxygen production.

Prevention of Obesity Through Principles of Ayurveda

Ayurveda, the ancient Indian system of medicine, is rooted in the principle of maintaining health through balance in body, mind, and spirit. It emphasizes preventive care through individualised dietary and lifestyle practices. This paper explores Ayurvedic principles to prevent obesity or Sthaulya, which is a leading lifestyle disorder contributing to a global health crisis, by focusing on classical texts and modern research. This paper aims to discuss preventive measures by addressing the root causes, which are physical, dietary, and psychological. Ayurveda offers a sustainable, holistic approach to health. Integrating these principles into modern health policies may significantly reduce obesity and related noncommunicable diseases.

Моделирование рабочего процесса гидравлического пульсатора манипулятора лесных машин

The article studies and simulates of the working process of the hydraulic pulsator used in the manipulators of forestry machines. Manipulator units of these machines play a key role in the performance of technological operations in the preparation of areas for growing forest crops, as well as in their subsequent maintenance. To increase the effi-ciency of operations such as cutting or removing unwanted tree and shrub vegetation, removing stones, boulders and other obstacles, the modernization of manipulators is an actual direction. One of the promising ways to reduce the en-ergy intensity of the working process is the introduction of highly effective vibration effects applied to the working bod-ies of the manipulator. The analysis of modern research in the field of hydraulic pulsators has shown that the devel-opment of new designs of rotary pulsators can significantly improve the performance indicators. In the course of the work, it has been revealed that the operating parameters of the hydraulic pulsator, such as the diameter of the spool shaft and the area of the working fluid overflow hole, depend on the maximum angle of rotation of the spool shaft axis equal to 22°30′. The permissible zones of variation of geometrical parameters of the specified orifice are deter-mined. Researches have shown, that change of area of an aperture for a fluid flow in time has a direct influence on the working fluid flow rate through the rod or piston cavity of the hydraulic cylinder. The greatest time of liquid over-flow (1-1.6 s) is observed at rotational speeds of the spool shaft 10-20 rpm. It is established that for holes with diameter of 5 mm in the zone of small rotational speeds the time of absence of liquid overflow increases by 0.18-0.36 s. For high-pressure hydraulic hoses with internal diameters of 8-16 mm, most often used in forestry machinery, the maxi-mum flow rate of working fluid is 0.00101 m³/s (1.01 l/s). The results are of practical importance for improving the designs of hydraulic pulsators and increasing the efficiency of forest machine manipulators.

Development of media literacy of students – future biotechnologists in the process of teaching mathematics

Introduction. One of the priority areas of modern mathematical education is the formation of a media-literate generation, whose professional activities are directly related to the prosperous existence of a person, in an era of unprecedented influence from the world of media. The purpose of the study is to identify and test the methodological conditions that ensure the development of media literacy of students – future biotechnologists in the process of teaching mathematics at the university. Materials and methods. The research involved 150 students of the Vyatka State University majoring in 19.03.01 Biotechnology training program. The main methods for measuring media literacy, presented by the New Media Literacy Scale (NMLS), was supplemented with diagnostic tools from specially designed contextual mathematical problems, based on real news reports. Statistical analysis of the obtained results was performed using the Pearson's χ2 test and the Mann-Whitney U test. KEYWORDS Results. The features of the formation and assessment of media literacy of students – future biotechnologists using mathematics based on modern research are presented for the first time. A number of methodological conditions have been formulated to ensure the development of this type of literacy, which clarifies and expands the understanding of the system of mathematical training for bachelor biotechnologists. Of primary importance for the development of media literacy skills is the solution of problems compiled on the basis of authentic media texts that are directly related to the social, professional and personal lives of students. Attention is also paid to data visualization, building mathematical models, mastering the apparatus of mathematical statistics, and using online Math tools. Additionally, diagnostic tools have been developed and tested. Its key feature is that the student does not work in a simulated environment, but in a real socio-scientific problem of the incidence of COVID-19. The effectiveness of the intervention based on the described conditions was confirmed by significant differences (Uemp. = 83; p &lt; 0,01). Conclusion. The identified methodological conditions and the proposed diagnostic tools can be used to develop media literacy skills of students of natural sciences in the process of teaching mathematics at a university.

On the instrumental meaning of communication

Introduction. Modern research is characterized by diverse, often contradictory, interpretations of the communication process and an extraordinary variety of terminology. This applies, among other things, to the interpretation of instrumental characteristics of communication. Purpose setting. The task of the research is to consider communication as a tool of cognition and as a tool for the transformation of an integratively understood environment. Methodology and methods of the study. The article examines communications from the point of view of studying their instrumental characteristics. The authors believe that the unity and contradiction of communication with industrial relations is manifested precisely in the instrumental nature of communication. Considering communication within the framework of such a methodology, we will see the possibility and necessity of changing approaches to communication research. According to the authors, the instrumental nature of communication is best revealed in the context of the division of labor (production). Results. The authors consider the process of communication formation in a logical aspect and come from the simplest natural attitude to a specifically human one through consideration of expedient activity (labor) and its division. The approach used by the authors allows us to define the boundary of the concept of «communication», which is revealed during the transition from the consideration of the technological division of labor to the consideration of the social division of production. The authors find a historical and philosophical analogy of the described process in the early works of K. Marx, where the concept of «communication relations» was present, which later transformed into the concept of productive forces. Conclusion. Communication functions are defined as the coordination of goals (results, products) of technologically separated labor processes, which means their connection. However, when separating management into a separate work process, the goal may not be agreed with the performer. When we move to the level of the whole society, we are no longer talking about the instrumental characteristics of communications, since at the level of the whole society, the coordination or opposition of interests occurs in the form of ideology.

Traditional Ethnomedical and Ethnobotanical Applications and Uses of Piper Nigrum

Ethnomedicine and ethnobotany have been at the forefront of current scientific focus. The focus of this review is Piper nigrum, for which there exists a wide host of traditional ethnomedical and ethnobotanical applications, recorded mostly from India and the surrounding regions where black pepper is native. These applications cover a wide range of pathologies, including cardiovascular, pulmonary, gastrointestinal, gynaecological, endocrine, integumentary and neurological, and viral diseases and colds. While some of these applications are confirmed by modern research, the majority have not been tested using modern scientific methods, and perhaps many more applications remain to be documented. Finally, it must be noted that some interesting non medical applications comprise the application of black pepper, as an insecticide/larvicide, are worth further consideration, especially given the newer policies at a European and international level.

Inorganic Nanoparticles-based Drug Delivery Systems for Neurodegenerative Diseases Therapy.

Neurodegenerative disorders (NDs) are highly prevalent among the aging population. It primarily affects the central nervous system (CNS), but the effects are also observed in the peripheral nervous system. Neural degeneration is a progressive loss of structure and function of neurons, which may ultimately involve cell death. The blood-brain barrier (BBB), which separates peripheral blood circulation from the central nervous system, is essential for maintaining intracerebral homeostasis. Drug delivery systems based on nanomaterials (NDDSs) employ nanoparticles (NPs) as their drug transport vehicles. Moreover, nanotechnologybased methods usually involve numerous nanosized carrier platforms, which potentiate the effect of the therapeutic agents in the therapy of NDs, especially in diagnosis and drug delivery, with negligible side effects. In addition, nanotechnology-based techniques have offered several strategies to cross BBB to intensify the bioavailability of drug moieties in the brain. In the last few years, diverse kinds of nanoparticles (NPs) have been developed by incorporating various biocompatible components (e.g., polysaccharide-based NPs, polymeric NPs, selenium NPs, AuNPs, protein-based NPs, gadolinium NPs, etc.), that showed great therapeutic benefits against NDs. The discussion concluded with a look at the opportunities and problems that come with NDDSs in modern basic and clinical research.

Transition state structure detection with machine learningś

Transition structure calculations via quantum chemistry methods have become a staple in modern chemical reaction research. Yet, success rates in optimizing transition structures rely heavily on rational initial guesses and expert supervision. We develop a machine learning approach that utilizes a bitmap representation of chemical structures to generate high-quality initial guesses for modeling transition states of chemical reactions. The core of the approach comprises a convolutional neural network methodology with a genetic algorithm. An extensive dataset derived from quantum chemistry computations is built, providing sufficient data on which the model can be trained, validated and tested. By applying the method to typical bi-molecular hydrogen abstraction reactions involving hydrofluorocarbons, hydrofluoroethers, and hydroxyl radicals—reactions critical in atmospheric fluoride degradation and global warming potential evaluation, yet extremely challenging to model, we achieve transition state optimizations with an impressive, verified success rate of 81.8% for hydrofluorocarbons and 80.9% for hydrofluoroethers. The reported work demonstrates the effectiveness of employing visual representation in chemical space exploration tasks and opens new avenues for the transition structure modeling.

ОСОБЕННОСТИ ИЗМЕНЕНИЯ БИОХИМИЧЕСКИХ ПОКАЗАТЕЛЕЙ КРОВИ КРЫС В УСЛОВИЯХ РАЗНЫХ ЭКСПЕРИМЕНТАЛЬНЫХ МОДЕЛЕЙ АЛЛОКСАН-ИНДУЦИРОВАННОГО ДИАБЕТА

The necessity of modern research lies in the use of reliable experimental models of diabetes mellitus (DM) in animals, both for understanding the pathogenesis of the disease and for developing new pharmacological and non-pharmacological treatment methods. In experimental practice, the chemical model of DM, including the use of alloxan, is the most widespread. This model induces pronounced metabolic disorders in rats, accompanied by a persistent increase in blood glucose levels. Objective of the study: to identify the features of biochemical changes in the blood of rats with alloxan-induced DM in different experimental models. Alloxan-induced diabetes was induced in male Wistar rats (n=71) of average weight (272.32±22.70 g) and age (150.00±12.00 days) by intraperitoneal administration of alloxan monohydrate at doses of 150 mg/kg (2-All150; n=29), 200 mg/kg (3-All200; n=19), and 300 mg/kg (4-All300; n=13; fractionally, 3 times, 100 mg/kg every other day). Rats in group 1 (control, n=10) received an equivalent volume of physiological saline (0.2 ml). During the development of DM, body weight and peripheral blood glucose levels (from the tail tip) were measured dynamically on days 7, 14, 21, 28, and 31. After the experiment was concluded (day 32), key biochemical parameters were measured in blood serum, including glucose, total cholesterol, high- and low-density lipoproteins, triglycerides, total protein, urea, creatinine, and C-reactive protein. The measurements were performed using an automated biochemical analyzer ERBA-XL-180 («ErbaLachema», Czech Republic) with proprietary reagent kits designed for this device. The significance of differences between groups was assessed using Dunn’s nonparametric test. The results of the study showed that the mortality rate of experimental animals depended on the dose of alloxan and the administration method (single or fractional). In the second group (All150), mortality was 44.83 %; the highest was in the third group (All200) at 47.36 %; and the lowest was in the fourth group (All300) with fractional administration at 30.77 %. One month after alloxan administration, the animals developed DM, which was accompanied by polydipsia, polyuria, hyperglycemia, ketonuria, weight loss, dulling, darkening, and shedding of fur. The maximum increase in blood glucose concentration in group 4 rats was observed at the earliest stage (day 7; 20.3 mmol/L), while in group 3 rats, it peaked on day 14 (27.4 mmol/L). Changes in the biochemical parameters of rat serum in all experimental groups indicated significant disturbances in carbohydrate, lipid, and protein metabolism. However, the severity of these changes depended on the experimental model and the alloxan dose: fractional administration of alloxan at a dose of 300 mg/kg resulted in the most pronounced metabolic disturbances, while significantly reducing mortality.

LabOps: A flexible self-hosted workflow of open source tools for efficient collaboration within research laboratories.

Effective collaboration, essential for success in academic environments, often requires efficient team communication and access to a team-oriented digital infrastructure. Despite the significance of efficient and effective collaboration within the academy, a standardized and structured suite for collaboration remains relatively overlooked. In the context of research labs, where multiple levels of collaboration often coexist, the ability to communicate and share resources in a timely and secure manner is critical. Modern research teams and institutions have historically attempted to solve these needs through proprietary, largely restrictive, and inflexible tools. Free and Open Source Software (FOSS) has facilitated the development of our modern computer-focused world by virtue of its legal, customizable, and accessible nature. However, FOSS remains weakly used for supporting communication, collaborative writing, storage, and other tasks within research labs. This paper discusses the implementation of a FOSS computational workflow for active collaboration within academic environments. We focus on identifying available tools that can support collaborative writing, instant messaging, data storage, among other tasks. The Lab Operations (LabOps) workflow presented in this paper-which can be self-hosted, adapted, and adopted at different levels-offers an alternative approach to off-the-shelf proprietary solutions for both within- and cross-lab communication. We discuss the benefits, flexibility, limitations, and potential approaches to adoption of the workflow.

Formononetin suppresses colitis-associated colon cancer by targeting lipid synthesis and mTORC2/Akt signaling.

Formononetin suppresses colitis-associated colon cancer by targeting lipid synthesis and mTORC2/Akt signaling.

Physical education teaching design under the STEAM concept using the convolutional neural network

With the continuous progress of science and technology and the increasing complexity of tasks, traditional physical education (PE) teaching methods are becoming insufficient to meet modern research demands. This work aims to design an efficient deep learning (DL) model for PE teaching under the Science, Technology, Engineering, Arts, and Mathematics (STEAM) educational concept. Based on the convolutional neural network (CNN), this work designs a CNN–STEAM model and then evaluates and compares this model with traditional CNN and Residual Network (ResNet) models in terms of basic and prediction performance. Indicators such as accuracy, recall, F1 score, and response time are used to quantify model performance. Through extensive experiments and data analysis, it is found that the CNN–STEAM model achieves significant improvements in all performance indicators, particularly with over 20% increases in accuracy, recall, and F1 score, along with reduced response times. The main contribution of this work is the successful design and validation of an efficient CNN–STEAM model, which demonstrates excellent performance in data processing and analysis within the field of PE teaching. This achievement not only provides robust technical support for researchers and technicians in PE but also offers new insights and methods for applying DL in the domain.

СТРУКТУРАЛИЗМ КАК МЕТОД ИССЛЕДОВАНИЯ ПРОЗЫ И ДРАМАТУРГИИ А.П.ЧЕХОВА

The article contains an exposition of the main provisions of the literary method of analyzing a literary text as structuralism. It allows you to find out the features of the artistic style of the author of the work through its composition, plot, linguistic originality and other specific features. The essence of the structural method is described by A.I.Ivanov, who refers to it as "hermetically forgotten education from outside invasions" that does not take into account the external connections of the literary text. L.M. Krupchanov considers immanence important in the structural analysis of a literary work, drawing the attention of researchers to study the object as a "closed system, without any context." At the same time, the literary theorist advises to perceive an artistic work as a phenomenon. In the proposed article, the authors consider the principles and methods of analyzing the literary text of A.P.Chekhov's prose and drama from the perspective of structuralism. Special attention is paid to the semantic openness of A.P.Chekhov's prose, which is manifested in her poetics. The analysis also includes the study of artistic details such as the fragmentary nature of the presented reality, the rejection of the dominant author's position, the unfinished ending, and the enumeration of third-rate inactive characters. Modern researcher A. Zakharyan calls such artistic features in the style of Anton Chekhov "immersion in the process of narration", "throwing the action far ahead". The use of such a "technology" in constructing the poetics of a work of art gives the author the opportunity to create its deep meanings.