Search Results (13,046)

This scientific article examines the issue of the effectiveness of digital transformation in Kazakhstan’s industry from the perspective of how effectively enterprises are able to convert digital resources into economically measurable results in the context of the transition to a model of sustainable industrial growth. The aim of the study is to develop a comprehensive methodology for assessing the digital readiness of industrial enterprises to implement and adapt digital ecosystems based on a synthesis of conceptual and empirical approaches. The methodology developed by the authors combines a parametric diagnostic system and stochastic frontier analysis (SFA) tools, which allows for a quantitative assessment of not only the scale but also the effectiveness of digital transformations at the regional level. The empirical part of the study includes statistical data for 2023, reflecting the dynamics of the introduction of ICT, cloud technologies, big data analytics, etc., in the industrial sector. The results of the analysis showed the steady development of digitalization with the existing pronounced spatial asymmetry. The application of SFA made it possible to identify technological “frontiers” and reveal the hidden potential for increasing the effectiveness of digital investments at the regional level. The practical value of the study lies in its applicability for assessing the digital readiness of industrial enterprises for ecosystem adaptation, diagnosing regional digital disparities, and justifying targeted government policy measures aimed at strengthening the digital maturity and sustainability of the industrial sector. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide, with patient outcomes highly dependent on early and accurate diagnosis. However, existing diagnostic methods, such as colonoscopy, fecal occult blood testing, and imaging, are often invasive, costly, or lack sufficient sensitivity and specificity, particularly in early-stage disease. In this context, aptamers, which are synthetic single-stranded oligonucleotides capable of binding to specific targets with high affinity, have emerged as a powerful alternative to antibodies for biosensing applications. This review provides a comprehensive overview of aptamer-based strategies for CRC detection, spanning from biomarker discovery to clinical translation. We first examine established and emerging CRC biomarkers, including those approved by regulatory agencies, described in patents, and shared across multiple cancer types. We then discuss recent advances in aptamer selection and design, with a focus on SELEX variants and in silico optimization approaches tailored to CRC-relevant targets. The integration of aptamers into cutting-edge sensing platforms, such as electrochemical, optical, and nanomaterial-enhanced aptasensors, is highlighted, with emphasis on recent innovations that enhance sensitivity, portability, and multiplexing capabilities. Furthermore, we explore the convergence of aptasensing with microfluidics, and wearable technologies to enable intelligent, miniaturized diagnostic systems. Finally, we consider the clinical and regulatory pathways for point-of-care implementation, as well as current challenges and opportunities for advancing the field. By outlining the technological and translational trajectory of aptamer-based CRC diagnostics, this review aims to provide a roadmap for future research and interdisciplinary collaboration in precision oncology. Full article

Background: Proliferative diabetic retinopathy (PDR) is a vision-threatening complication of diabetes characterized by retinal neovascularization. Predicting which diabetic patients will develop PDR remains challenging. Measuring mRNA expression levels may help elucidate the molecular pathways involved in PDR pathogenesis. This study investigated the expression of genes related to inflammatory and proliferative pathways in the peripheral blood of patients with PDR, compared to patients with non-proliferative diabetic retinopathy (NPDR) and healthy controls, using NanoString technology. The findings may aid in identifying potential biomarkers and therapeutic targets for early intervention. Methods: This prospective study was approved by the institutional ethics review board, and written informed consent was obtained from all participants. The study included patients with PDR (n = 9), NPDR (n = 8), and non-diabetic controls (n = 6). Total RNA was extracted from whole blood samples using the MagNA Pure Compact RNA Isolation Kit (Roche Ltd., Basel, Switzerland) and analyzed with the NanoString platform (Agentek Ltd., Yakum, Israel). Results: Expression levels of 578 genes across 15 signaling pathways, including inflammation (e.g., IL-17, TNF, and NF-κB) and cancer-related PI3K-Akt pathways, were evaluated. Sixty-six genes (11.5%) were differentially expressed (p < 0.05) between the PDR group and the NPDR and control groups. The most prominently overexpressed genes in PDR included TGFβ1, TGFβ1R, IL23R, BAX, and CFB, which were primarily involved in inflammatory and proliferative signaling. Conclusions: Gene expression profiling using NanoString technology revealed significant upregulation of genes related to inflammation and proliferation in patients with PDR. These findings suggest that beyond angiogenesis, inflammatory and proliferative pathways may play a central role in PDR development and could serve as targets for novel therapeutic strategies. Full article

Smart mobility is widely promoted as a solution to urban congestion, pollution, and inefficiency. Yet, its adoption remains inconsistent, particularly in developing and small cities. While prior research has examined technological enablers, the structural and systemic barriers that constrain adoption are less understood. This study identifies and analyzes the institutional, political, technological, and socio-cultural barriers that collectively inhibit smart mobility transitions. Using Total Interpretive Structural Modelling (TISM) and MICMAC analysis, the study hierarchically maps 14 interrelated barriers derived from literature and validated through expert consultation. Findings reveal that legacy paradigms in conventional transport planning, fragmented institutional mandates, and regulatory misalignment are the foundational constraints that reinforce downstream challenges such as affordability, limited service coverage, and user resistance. Anchored in Critical Urban Theory, the study reframes smart mobility adoption as a contested and political process shaped by institutional inertia and unequal access to technology. The paper contributes to the literature by offering a theory-informed diagnostic framework for understanding mobility transitions. It also provides practical entry points for policymakers, planners, and mobility innovators seeking to target root cause interventions rather than symptoms, to enable more equitable, scalable, and resilient smart mobility transitions. Full article

In less than 30 years, Deep Brain Stimulation (DBS) has evolved from an antiparkinsonian rescue intervention into a flexible neuromodulatory therapy with the potential for personalized, adaptive, and enhancement-focused interventions. In this review we collected evidence from seven areas: (i) modern eligibility criteria, and ways to practically improve on these, outside of ‘Core Assessment Program of Surgical Interventional Therapies in Parkinson’s Disease’ (CAPSIT-PD); (ii) cost-effectiveness, where long-horizon models now show positive incremental net monetary benefit for Parkinson’s disease, and rechargeable-devices lead the way in treatment-resistant depression and obsessive–compulsive disorder; (iii) anatomical targets, from canonical subthalamic nucleus (STN) / globus pallidus internus (GPi) sites, to new dual-node and cortical targets; (iv) mechanistic theories from informational lesions, antidromic cortical drive, and state-dependent network modulation made possible by optogenetics and computational modeling; (v) psychiatric and metabolic indications, and early successes in subcallosal and nucleus-accumbens stimulation for depression, obsessive–compulsive disorder (OCD), anorexia nervosa, and schizophrenia; (vi) procedure- and hardware-related safety, summarized through five reviews, showing that the risks were around 4% for infection, 4–5% for revision surgery, 3% for lead malposition or fracture, and 2% for intracranial hemorrhage; and (vii) future directions in connectomics, closed-loop sensing, and explainable machine learning pipelines, which may change patient selection, programming, and long-term stewardship. Overall, the DBS is entering a “third wave” focused on a better understanding of neural circuits, the integration of AI-based adaptive technologies, and an emphasis on cost-effectiveness, in order to extend the benefits of DBS beyond the treatment of movement disorders, while remaining sustainable for healthcare systems. Full article

This review focuses on hydrogel-based systems specifically designed for non-opioid analgesics, aiming to improve efficacy, safety, and translational applicability. The opioid crisis has intensified the need for safer and more effective alternatives in pain management. Non-opioid analgesics including NSAIDs, acetaminophen, gabapentinoids, antidepressants, anticonvulsants, NMDA receptor antagonists, topical agents, and cannabinoids offer promising options but are limited by rapid clearance, short half-lives, and off-target effects. Hydrogel-based drug delivery systems present a novel solution by enabling controlled, localized, and sustained release of analgesics, thus improving therapeutic efficacy and minimizing systemic toxicity. Advances in stimulus-responsive, self-healing, mechanically robust, and hybrid or nanocomposite hydrogels have broadened their biomedical applications and clinical relevance. This narrative review summarizes key hydrogel technologies and their integration with non-opioid analgesic agents. We explore encapsulation strategies, drug release mechanisms, and emerging clinical data, while also addressing critical challenges such as biocompatibility, mechanical durability, and translational scalability. Interdisciplinary collaboration between material scientists, clinicians, and regulatory experts is essential to advance hydrogel-based therapies from bench to bedside. Overall, hydrogel platforms hold transformative potential in optimizing non-opioid analgesic delivery and redefining the future of pain management. Full article

In recent years the global market of nanomedicine has experienced incredible growth owing to the advances in the field. This translation of the technique to the biomedical industry requires the development of production methods that deliver nanomedicines with a high degree of reproducibility between batches, combined with cost and time efficiency. The use of nanoparticles in medicine usually requires their surface functionalization to improve biocompatibility in addition to providing targeting capacities and/or stimuli-responsive behavior, among other interesting skills. Microfluidic technology has revolutionized the field both in nanomedicine synthesis and in preclinical evaluation. However, microfluidic-assisted synthetic procedures commonly require high-cost methods and equipment to fabricate the microreactors. The aim of this work is to present an ultra-low-cost microfluidic platform that permits the versatile modification of nanomaterials. To prove this approach, two different model nanoparticles with different natures: soft nanoparticles (liposomes) and rigid nanoparticles (mesoporous silica) have been decorated both with small molecules and with other nanoparticles, respectively, in order to evaluate the scope of this approach. The anchoring of the covalently attached elements has been performed using click chemistry, in compliance with the principles for further transfer to the drug industry. Full article

Depression is becoming more common in the face of modern life’s obstacles. Antidepressants are a fast-expanding pharmaceutical category. Antidepressant residues in water must be closely monitored and kept at levels that do not endanger human health, just like those of other psychotropic medications. Additionally, research has shown that these pollutants severely hinder aquatic life’s ability to migrate, reproduce, and interact with one another when they enter natural ecosystems. Antidepressants released into the natural environment can therefore be expected to have an impact on exposed fish and other aquatic species. There is a lot of information available about how exposure affects fish, but much of it is for exposure levels higher than those seen in their natural habitats. Antidepressants can bioaccumulate in fish tissues, and some behavioral effects have been documented for exposures that are relevant to the environment. As a result, antidepressant residue removal methods must be incorporated into contemporary wastewater treatment plant technology. In addition to covering a wide range of suggested treatment options and their ecotoxicological consequences on non-target organisms, this study discusses recent efforts to accomplish this goal. First, a thorough analysis of the harmful impacts on non-target people is provided. This work describes a variety of adsorptive methods that can make use of modern materials like molecularly imprinted polymers or ion-exchange resins or can rely on well-known and efficient adsorbents like silicates or activated carbon. Although extractive methods are also taken into consideration, they are now impractical due to the lack of reasonably priced and ecologically suitable solvents. Lastly, sophisticated oxidation methods are discussed, such as electrochemical alternatives, UV and gamma radiation, and ozone therapy. Notably, some of these techniques could totally mineralize antidepressant toxicants, either alone or in combination. Lastly, the topic of biological treatment with microorganisms is covered. This method can be very specific, but it usually prevents full mineralization. Full article

Background/Objectives: Thrombotic diseases, such as ischemic stroke, acute myocardial infarction, and venous thromboembolism, are leading causes of global morbidity and mortality. Traditional thrombolytic therapies like systemic tissue plasminogen activator (tPA) are limited by bleeding risks, poor targeting, and inconsistent efficacy. This review explores emerging non-pharmacological technologies aimed at overcoming these challenges through targeted, minimally invasive thrombolysis. Methods: A narrative synthesis of recent advancements was conducted, focusing on six innovative approaches: ultrasound-mediated thrombolysis (UMT), microrobots, electrothrombectomy, photothrombectomy, magnetic targeted thrombolysis, and nanotechnology. Preclinical and clinical studies were reviewed to assess mechanisms, efficacy, safety, and translational potential, prioritizing technologies with demonstrated success in animal or early human trials. Results: Technologies like microbubble-enhanced UMT, magnetically actuated microrobots, and fibrin-targeted nanoparticles showed promising results. UMT improved recanalization in ischemic stroke and pulmonary embolism, while electrothrombectomy demonstrated safe, effective clot extraction in human trials. However, challenges remain in scalability, biocompatibility, and clinical integration, with microrobots and photothrombectomy still in preclinical stages. Conclusions: Emerging thrombolysis technologies offer safer, more targeted alternatives to conventional treatments. Clinical adoption will depend on overcoming translational hurdles, including large-scale trials, miniaturization, and interdisciplinary collaboration, with a focus on hybrid approaches and real-time imaging integration. Full article

The application of orchard inspection robots has become increasingly widespread. How-ever, achieving autonomous navigation in unstructured environments continues to pre-sent significant challenges. This study investigates the Simultaneous Localization and Mapping (SLAM) navigation system of an orchard inspection robot and evaluates its performance using Light Detection and Ranging (LiDAR) technology. A mobile robot that integrates tightly coupled multi-sensors is developed and implemented. The integration of LiDAR and Inertial Measurement Units (IMUs) enables the perception of environmental information. Moreover, the robot’s kinematic model is established, and coordinate transformations are performed based on the Unified Robotics Description Format (URDF). The URDF facilitates the visualization of robot features within the Robot Operating System (ROS). ROS navigation nodes are configured for path planning, where an improved A* algorithm, combined with the Dynamic Window Approach (DWA), is introduced to achieve efficient global and local path planning. The comparison of the simulation results with classical algorithms demonstrated the implemented algorithm exhibits superior search efficiency and smoothness. The robot’s navigation performance is rigorously tested, focusing on navigation accuracy and obstacle avoidance capability. Results demonstrated that, during temporary stops at waypoints, the robot exhibits an average lateral deviation of 0.163 m and a longitudinal deviation of 0.282 m from the target point. The average braking time and startup time of the robot at the four waypoints are 0.46 s and 0.64 s, respectively. In obstacle avoidance tests, optimal performance is observed with an expansion radius of 0.4 m across various obstacle sizes. The proposed combined method achieves efficient and stable global and local path planning, serving as a reference for future applications of mobile inspection robots in autonomous navigation. Full article

Recent advances in bionic intelligence are reshaping humanoid-robot design, demonstrating unprecedented agility, dexterity and task versatility. These breakthroughs drive an increasing need for large scale and high-quality data. Current data generation methods, however, are often expensive and time-consuming. To address this, we introduce Digital Twin Loong (DT-Loong), a digital twin system that combines a high-fidelity simulation environment with a full-scale virtual replica of the humanoid robot Loong, a bionic robot encompassing biomimetic joint design and movement mechanism. By integrating optical motion capture and human-to-humanoid motion re-targeting technologies, DT-Loong generates data for training and refining embodied AI models. We showcase the data collected from the system is of high quality. DT-Loong also proposes a Priority-Guided Quadratic Optimization algorithm for action retargeting, which achieves lower time delay and enhanced mapping accuracy. This approach enables real-time environmental feedback and anomaly detection, making it well-suited for monitoring and patrol applications. Our comprehensive framework establishes a foundation for humanoid robot training and further digital twin applications in humanoid robots to enhance their human-like behaviors through the emulation of biological systems and learning processes. Full article

The detection of high-consequence viral pathogens is essential for spillover prevention and reduction in transmission but is limited by the low sensitivity of next-generation sequencing technology. Low-titer field samples from a variety of hosts are primarily composed of non-viral genomic material, reducing the probability of obtaining usable sequence data. Targeted enrichment, such as VirCapSeq-VERT, removes background genomic material to improve virus detection but is mainly used for sequencing clinical samples. We customized the VirCapSeq-VERT probe system to aid in the detection of zoonotic viruses of interest and adapted it for use on the Oxford Nanopore sequencing platform. We validated the method on a variety of samples, including a mock virome consisting of seven RNA viruses, samples from an animal laboratory study, and a set of animal field samples. We also developed Nanite, a lightweight bioinformatics pipeline, to perform bioinformatic analyses. Results indicated that the optimized enrichment protocol improved sequencing by enhancing the detection of viruses, increasing read lengths, and, in some cases, improving genomic coverage. Most importantly, the sequencing of zoonotic viruses was improved in field samples with low titers, suggesting that this protocol is a useful tool for increasing the efficacy of Oxford Nanopore sequencing for field-oriented applications. Full article

This study integrates network toxicology with molecular docking technology to systematically elucidate the key molecular mechanisms and signaling pathways by which bisphenol A (BPA) induces obesity. By cross-referencing multiple databases—including the Comparative Toxicogenomics Database (CTD), SwissTarget prediction platform, and PharmMapper—potential BPA target genes were identified, yielding a total of 1326 candidate targets. Obesity-related genes were collected from GeneCards and OMIM databases, yielding 4570 disease-associated targets. Among these, 653 overlapping genes were identified as potential mediators linking BPA exposure to obesity. Protein interaction networks were constructed using STRING and Cytoscape, and the MCC algorithm identified five core hub genes: STAT3, MYC, TP53, IL6, and mTOR. Validation using random datasets demonstrated significant upregulation of these genes in the obesity group (p < 0.05), highlighting their potential central role in BPA-induced obesity effects. Functional enrichment analysis via GO and KEGG pathways indicated that BPA may promote obesity by interfering with endocrine signaling, activating lipid metabolism, and stimulating atherosclerosis pathways. Molecular docking analysis using CB-Dock2 confirmed strong binding affinity between BPA and core targets, providing structural evidence for their potential interactions. This study elucidates the potential biological mechanism by which BPA exacerbates obesity through endocrine disruption and metabolic reprogramming, employing a multidimensional approach encompassing cross-target analysis, pathway enrichment, and molecular interactions. It provides an innovative systems toxicology framework and empirical basis for assessing metabolic health risks induced by environmental pollutants. Full article

The decarbonization of shipping and shipbuilding is a critical challenge under the Inter-national Maritime Organization’s (IMO) 2030 greenhouse gas (GHG) reduction target and 2050 net-zero strategy, requiring effective coordination between policy and technology. This study investigates how Japan, China, and Korea respond to these regulatory pressures by systematically analyzing their policy–technology linkages. A four-stage design was applied, combining qualitative case studies, policy–technology mapping, theoretical interpretation, and comparative analysis, to trace how national strategies shape eco-friendly transitions. Japan employs an innovation-led, institution-convergent model in which technological demonstrations drive institutional adaptation and diffusion, China follows a policy-designated, execution-oriented model where state-led interventions accelerate commercialization, and Korea adopts a coordination-based, cyclical model balancing public demonstrations, financial support, and international standardization to reduce transition costs. These findings demonstrate that sequencing between policy–technology linkage is context-dependent, shaped by technological maturity, economic feasibility and infrastructure, institutional predictability, and socio-environmental acceptance. The study contributes a cyclic co-evolutionary perspective that moves beyond technological or institutional determinism, reconceptualizes regulation as enabling infra-structure, and identifies implications for global standard-setting and industrial competitiveness. The insights inform practical strategies for major shipbuilding nations to reduce costs while sustaining competitiveness under the IMO’s decarbonization framework. Full article

The use of insects for feed has a significant impact on aquaculture, contributing to the achievement of the Sustainable Development Goal of Zero Hunger and Sustainable Agriculture (SDG 2), among others. This study mapped the intermediate Technology Readiness Levels (TRLs), encompassing scientific knowledge (TRL 3) through 971 scientific articles (Scopus) and technological development (TRLs 4–5) through 218 patents (Espacenet). The highest conversions from TRL 3 to TRLs 4–5 were observed for fish, mollusks, crustaceans, and annelids. Key technological targets include carp and black soldier flies (BSF). Most technologies follow circular economy principles. Emerging themes include immunity, cloning, molecular techniques, metabolomics, and genetics. China leads in TRLs 3–5, followed by the United States. Only France, the United States, and five additional countries hold export-oriented patents targeting 26 markets, primarily involving BSF-based feed formulations. Future growth trends are exponential for scientific articles, logarithmic for total patents, and linear for export patents. Collaboration at TRLs 4–5 remains limited, underscoring the need for greater international cooperation to expand access to sustainable insect-based aquaculture feed technologies. Full article