Strategic Advances Research Articles

Challenges and strategic advancements in platinum-based catalysts for tailored methanol oxidation reaction

Challenges and strategic advancements in platinum-based catalysts for tailored methanol oxidation reaction

Scientometric tools in strategising the development of scientific periodicals: the case of the journal Digital Models and Solutions

The present study is dedicated to the development of scientometric tools for the strategic advancement of a scientific periodical, exemplified by the journal of the Ural State University of Economics, “Digital Models and Solutions”. The research involved a compre hensive analysis of the publication activity and thematic profile of this journal, as well as a general statistical examination of Russian academic journals indexed in the Russian Science Citation Index (RSCI) that pertain to the upper echelon of the State Rubricator of Scientific and Technical Information category “Informatics”. Primary data collection was conducted using the platforms elibrary.ru, CyberLeninka and CrossRef. The data analysis and visuali zation were performed utilizing the R programming language. The construction of thematic networks was carried out using the VOSviewer software, while additional visualization of certain results was executed using Scimago Graphica. The findings of the study identify the current positioning of the journal “Digital Models and Solutions” among scientific publi cations in informatics, define target scientometric indicators for its prospective growth, and propose specific recommendations for the strategic development of the journal, aimed at enhancing its competitiveness and scholarly impact.

Driving National R&D: Methodological Insights into Developing a Classifier for the Ukrainian National CRIS System by the State Scientific and Technical Library of Ukraine

Objective. The objective of this study is to develop and characterize a comprehensive classifier for research and development (R&D), which plays a crucial role in the effective implementation of a National Current Research Information System (CRIS). The study aims to address the challenges and methodologies involved in creating a system that categorizes diverse R&D initiatives while ensuring interoperability with existing systems and adaptability to evolving scientific fields. Methods. The development of the classifier involved a multi-step process, including consultation with domain experts and reviewing existing classification systems. The study focused on identifying key research areas, ensuring compatibility with international standards, and developing a flexible taxonomy to cover both established and emerging fields. A diagnostic study on CRIS systems in Latin America and insights from similar systems, such as in Croatia and Portugal, were examined to refine the classifier's design for Ukraine. Results. The study successfully developed a classifier that addresses the specific needs of the Ukrainian research landscape, particularly within the Ukrainian Information System for Current Research (URIS). The classifier's structure aligns with international standards and supports interoperability with global databases. Furthermore, the dynamic nature of the classifier allows for continuous updates, making it adaptable to new research fields. The classification system was also tailored to accommodate Ukraine’s unique research ecosystem and infrastructure. Conclusions. The development of this R&D classifier represents a strategic advancement for Ukraine’s research infrastructure, enhancing data organization, accessibility, and collaboration. By addressing both technical and contextual challenges, the classifier provides a flexible, scalable solution that supports long-term scientific innovation. This study highlights the importance of context-driven approaches in creating effective research management tools, positioning the classifier as a robust framework for future developments in CRIS systems. The State Scientific Technical Library of Ukraine has played a pivotal role in developing this classifier, ensuring it meets the specific needs of the Ukrainian research community.

Integration of Blockchain-Based Decentralized Finance into Financial Planning and Analysis: A Framework for Corporate Finance Innovation

The integration of Decentralized Finance (DeFi) into Financial Planning and Analysis (FPA) systems marks a pivotal transformation in corporate financial management, presenting organizations with unprecedented opportunities for operational efficiency, risk management, and strategic advancement. This article provides a comprehensive examination of the implementation framework, challenges, and strategic implications of incorporating DeFi technologies into traditional FPA systems. The article analyzes the technical architecture required for successful integration, including smart contract implementation, decentralized liquidity mechanisms, and blockchain-based audit systems, while addressing critical considerations in regulatory compliance and organizational change management. The article reveals significant potential for cost reduction, improved process efficiency, and enhanced risk management capabilities through DeFi integration while highlighting the importance of robust security protocols and governance frameworks. The article also identifies emerging opportunities in artificial intelligence integration, cross-chain interoperability, and industry-specific applications, offering valuable insights for organizations navigating this technological transformation. Furthermore, the article examines implementation challenges and provides strategic solutions for organizations undertaking DeFi integration initiatives. The article demonstrates that while the integration process presents complex technical and organizational challenges, the potential benefits in terms of operational efficiency, cost reduction, and competitive advantage make it a compelling strategic initiative for forward-thinking organizations. This article contributes to the growing body of knowledge on DeFi implementation in corporate settings and provides practical guidelines for organizations seeking to leverage blockchain technology in their financial operations.

Ethereal Based Electrolytes for Ultrastable LiNi0.8Mn0.1Co0.1O2 (NMC811)||Si Full Cells

With its impressive specific capacity of 3579 mAh/g (when alloyed into Li15Si4 at room temperature), Silicon (Si) anode is widely regarded as an ideal alternative to graphite anodes. However, its commercial viability is still hampered by rapid capacity degradation. Liquid electrolytes based on ethereal solvents such as dimethoxyethane (DME) and diglyme (DG) have demonstrated excellent long-term cycling performance in Li||Si half cells. However, their utilization in full cells like LiNi0.8Mn0.1Co0.1O2 (NMC811)||Si remains limited due to their relatively low oxidation stability at the NMC811 side.In this investigation, innovative electrolyte systems employing Lithium bis(fluorosulfonyl)imide (LiFSI) salt were developed. Various ethereal solvents including DME, DG, 2,2-dimethyl-3,6,9,12-tetraoxa-2-silatridecane (1NM3), and self-synthesized 1,1,1-trifluoro-2-(2-(2-(2,2,2-trifluoroethoxy)ethoxy)ethoxy)ethane (FDG) were methodically examined. Initially, density functional theory (DFT) calculations were utilized to compare the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) levels of these solvents, revealing that 1NM3 and FDG exhibited lowered HOMO levels, suggesting enhanced oxidative stability on the NMC811 cathode side compared to DME and DG. Subsequently, the solvation structure of the prepared electrolyte systems was investigated via Fourier Transform Infrared Spectroscopy (FTIR). The addition of a -CF3 functional group and the weaker dissociation capacity of FDG resulted in significant cation-anion aggregates (AGGs) within the FDG-based electrolytes, while no such AGGs were observed in the DME, DG, and 1NM3-based electrolytes. Electrochemical properties and performances were further evaluated through systematic tests on Li||Al, Li||Si half cells, and LiNi0.8Mn0.1Co0.1O2 (NMC811)||Si full cells. Differential capacity (dQ/dv) profiles from Si||Li half cells revealed their distinct reduction behavior on the Si anode. Potentiostatic hold tests on NMC811||Li half cells demonstrated the superior oxidative stability of FDG-based electrolytes up to 4.5 V vs. Li/Li+. Long-term cycling results confirmed significant improvements with 1NM3 and FDG solvents in NMC811||Si full cells, maintaining a high specific capacity of 900 mAh/g after 500 cycles for the FDG-based electrolytes. Further analysis of the interphases formed on electrodes via depth-profiling X-ray photoelectron spectroscopy (XPS) indicated enhanced oxidative stability on the NMC811 cathode and improved solid electrolyte interphase (SEI) on Si anodes, leading to enhanced electrochemical performance. Thus, our exploration of these ethereal electrolytes has paved the way for strategic advancements in crafting novel electrolytes specifically designed for Si anodes, highlighting their remarkable long-term cycling capabilities within NMC811||Si full cells.

North Africa in the Foreign Policy of Catherine II

The 18th century represented a transformative era for the Russian Empire, characterized by substantial internal reforms and notable foreign policy achievements. Amidst sweeping modernization efforts, Russia secured significant victories on the international stage. Under Peter I, Russia "opened a window" to Europe, while Catherine II's reign expanded Russia's geopolitical reach to the Black Sea, facilitating access to fertile southern territories and establishing crucial maritime routes for international trade. These strategic advancements considerably enhanced Russia's influence and strategic capacities. During Catherine II’s reign, Russia also initiated its first forays into North Africa, a region previously beyond the empire's strategic horizon. Prior to gaining maritime access to the Black and Mediterranean Seas, Russian interaction with North African territories was negligible. However, the geopolitical landscape of Catherine's era prompted the necessity of engaging with Egypt, Algeria, Morocco, Tunisia, and Tripoli.This article investigates the principal foreign policy initiatives of Russia toward North Africa during the latter half of the 18th century. These efforts served as ancillary operations to Russia's overarching conflict with the Ottoman Empire. Throughout the Russo-Turkish Wars, Russia exploited separatist movements within the Ottoman periphery to weaken its adversary strategically. In times of peace, Russian priorities shifted to safeguarding merchant vessels in the Mediterranean from attacks by Barbary corsairs—specifically from Tunisia, Algeria, and Tripoli. To mitigate these threats, Russia employed diplomatic pressure on the Sublime Porte and sought to negotiate peace agreements with North African states. Nevertheless, these early Russian engagements in North Africa were tentative and often marked by limited success and instances of diplomatic adventurism, leaving several initiatives unrealized.Utilizing archival documents from the Archive of Foreign Policy of the Russian Empire (AVPRI) and the Russian State Archive of Ancient Acts (RGADA), this article provides a detailed examination of Russia’s diplomatic decision-making and negotiations with North African states. While prior Russian and foreign scholarship has analyzed specific events and countries in this context, this study seeks to offer a more holistic understanding of Russia’s foreign policy objectives and actions in North Africa during the 18th century.

Business Analysis – A Case Study of Delta Cafés

This in-depth research digs into Delta Cafés' rich history, strategic advancements, and current strategies. The key goals of this paper are to unearth the historical milestones that have shaped Delta Cafés, analyze its present market positioning, and examine the leadership concepts that have been critical to its success. Our work strives to provide useful insights into Delta Cafés' journey of continual expansion, innovation, and the enduring ideals that characterize its essence through a comprehensive examination of the company's history. Our project looks into the compelling history and modern dynamics of a prominent Portuguese coffee brand by embarking on a trip through the rich tapestry of Delta Cafés. Delta Cafés' journey from its humble beginnings in a 50-square-meter warehouse in 1961 to its current global prominence displays an unwavering commitment to quality, innovation, and sustainability in the coffee industry.

A Survey of AI-Powered Proactive Threat-Hunting Techniques: Challenges and Future Directions

The study narrates the dimensions of AI-powered threat hunting techniques that keep changing and draws on their importance in cybersecurity measures while dealing with advanced cyber threats. While the cyber adversary is continuously adapting and innovating, the integration of advanced AI algorithms, including reinforcement learning and hybrid models, has become one of the key strategies for real-time threat detection and response. The research investigates the transformative potential of these algorithms to facilitate adaptive systems that can quickly recognize and act on new attack vectors. It also discusses the integration of AI with emergent technologies like blockchain, quantum computing, and IoT in the dimension of their potential to leverage threat intelligence and response mechanisms. This would naturally lead to increased efficiency in threat hunting by leveraging the strengths brought into this endeavor by both the AI systems and human analysts. The study also advocates for the development of strong policy and governance frameworks to drive home some ethical concerns in deploying AI in cybersecurity. Such a framework is very important for addressing challenges on data privacy, accountability, and transparency. The findings bring into sharp relief that, in this continuing evolution of the cybersecurity landscape, what will work best is a proactive stance-a proactive stance that incorporates innovative technologies with human ingenuity and ethics. This white paper broadly documents the considerable promise of AI in threat hunting and strategic advances needed to harden organizational defenses against a dynamic threat environment.

Revisiting the TAM: adapting the model to advanced technologies and evolving user behaviours

PurposeThe purpose of this study is to examine the applicability of the technology acceptance model (TAM) in libraries considering the advanced technologies and users’ behaviour.Design/methodology/approachThe research uses a critical reflective approach to review and synthesize a body of recent academic literature on the use of TAM in libraries. The review included assessing TAM’s historical evolution, its limitations and how it could be improved.FindingsThe findings indicated that, although TAM can be viewed as an appropriate theoretical model to explain the users’ intention towards technology acceptance, it is limited in explaining both the users’ attitude towards advanced technology and their behaviour in advanced library settings.Research limitations/implicationsTo enhance the practicality of TAM in libraries, several recommendations for strategic advancements have been proposed such as contextualizing TAM to libraries, exploring AI-driven adoption, integrating library-specific constructs, understanding cultural differences and using holistic research approaches.Originality/valueThe findings contribute to a deeper understanding of technology adoption in libraries and to the future possibilities of TAM.

Experimental evaluation and optimization of the heat pipes integrated thermoelectric generator using response surface methodology

In this study, integration of heat pipes with thermoelectric generators is proposed for the recovery of waste heat. Heat energy is transferred from a heat source to thermoelectric elements via heat pipes, enabling energy conversion. To dissipate excess heat from the system after conversion, additional heat pipes are positioned on the cold sides of thermoelectric elements. Cooling of the condenser sections of these heat pipes is facilitated using air flow provided by a fan. A novel approach in this study involves the innovative integration of heat pipes with thermoelectric generators. This integration provides a new pathway for optimizing waste heat recovery systems by combining advanced thermal management techniques with thermoelectric technology. Experiments conducted at different power inputs (12–42 W) and air velocities (0.4, 0.8, 1.2 m/s) determine the performance of the thermoelectric generator. Furthermore, a power usage efficiency analysis was conducted to discuss the applicability of the proposed method in electronics. At low air velocities, values below the ideal value of 1 were achieved. Experimental data were analyzed using response surface methodology to assess the impact of varying input parameters on the power output and efficiency of the thermoelectric generator. Optimization studies highlighted the importance of effectively cooling the cold side of thermoelectric elements. The highest power output and efficiency are achieved under conditions of 42 W power input, 1.2 m/s air velocity, and use of 4 heat sinks, yielding approximately 0.8 W and 2 %, respectively. Furthermore, the response surface methodology analysis indicated that the most significant effect on system outputs was the power input. Moreover, the results of this study lay the groundwork for future strategic advancements in thermoelectric generators, enhancing their role in sustainable energy solutions.

Strategic Advancement in Inner Filter Effect Controllable Detection of Tetracyclines and Nitroaromatics in Real-World Matrices by Two-Dimensional Coordination Polymer

Strategic Advancement in Inner Filter Effect Controllable Detection of Tetracyclines and Nitroaromatics in Real-World Matrices by Two-Dimensional Coordination Polymer

Strategic Advances in Combination Therapy for Metastatic Castration-Sensitive Prostate Cancer: Current Insights and Future Perspectives.

The contemporary treatment for metastatic castration-sensitive prostate cancer (mCSPC) has evolved significantly, building on successes in managing metastatic castration-resistant prostate cancer (mCRPC). Although androgen deprivation therapy (ADT) alone has long been the cornerstone of mCSPC treatment, combination therapies have emerged as the new standard of care based on recent advances, offering improved survival outcomes. Landmark phase 3 trials demonstrated that adding chemotherapy (docetaxel) and androgen receptor pathway inhibitors to ADT significantly enhances overall survival, particularly for patients with high-volume, high-risk, or de novo metastatic disease. Despite these advancements, a concerning gap between evidence-based guidelines and real-world practice remains, with many patients not receiving recommended combination therapies. The challenge in optimizing therapy sequences, considering both disease control and treatment burdens, and identifying clinical and biological subgroups that could benefit from personalized treatment strategies persists. The advent of triplet therapy has shown promise in extending survival, but the uro-oncology community must narrow the gap between evidence and practice to deliver the most effective care. Current research is focused on refining treatment approaches and utilizing biomarkers to guide therapy selection, aiming to offer more personalized and adaptive strategies for mCSPC management. Thus, aligning clinical practices with the evolving evidence is urgently needed to improve outcomes for patients facing this incurable disease.

Porous Metal Organic Framework (MOF) derived dimorphic (n-ZnO/p-NiO) Z-scheme heterojunction anchored with MWCNTs (ternary nano-architecture): A novel approach for optimization of photodegradation mechanism and kinetics of Congo red (CR) dye

Global efforts to combat water pollution, especially from organic dyes like Congo red, emphasize the use of advanced nanomaterials for sewage purification. Metal-Organic Frameworks (MOFs), known for their crystalline structures and versatile properties, have become pivotal in wastewater treatment research. Integrating MWCNTs into MOF derived composite nanostructures is a strategic advancement, boosting the efficiency of photocatalytic systems and addressing environmental concerns. This study details the synthesis of a novel Z-scheme heterojunction nanocomposite (n-ZnO/p-NiO) incorporating multi-walled carbon nanotubes (MWCNTs), achieved via a solvothermal method using metal-organic framework (MOF) as a template. The study uses XRD, FTIR, FESEM, BET, UV, and PL for comprehensive nanocomposite characterization, offering insights into its structural, morphological, and optical properties. The resultant nanocomposite displays high surface area, sturdy pore arrangement, and consistent morphology. MWCNTs influence crystal growth and optical absorption, enhancing surface hydroxyl group concentration and acting as electron acceptors. This results in decreased photo oxidation and improved overall stability under light exposure in the composite. The composite achieves 92 % Congo red degradation in 60 min under UV light, showcasing superior dye adsorption capacity. This underscores its potential as an efficient photocatalyst for environmental remediation and wastewater treatment.

Inhibition of IRP2-dependent reprogramming of iron metabolism suppresses tumor growth in colorectal cancer

BackgroundDysregulation of iron metabolism is implicated in malignant transformation, cancer progression, and therapeutic resistance. Here, we demonstrate that iron regulatory protein 2 (IRP2) preferentially regulates iron metabolism and promotes tumor growth in colorectal cancer (CRC).MethodsIRP2 knockdown and knockout cells were generated using RNA interference and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 methodologies, respectively. Cell viability was evaluated using both CCK-8 assay and cell counting techniques. Furthermore, IRP2 inhibition was determined by surface plasmon resonance (SPR) and RNA immunoprecipitation (IP). The suppressive effects of IRP2 were also corroborated in both organoid and mouse xenograft models, providing a comprehensive validation of IRP2’s role.ResultsWe have elucidated the role of IRP2 as a preferential regulator of iron metabolism, actively promoting tumorigenesis within CRC. Elevated levels of IRP2 expression in patient samples are correlated with diminished overall survival, thereby reinforcing its potential role as a prognostic biomarker. The functional suppression of IRP2 resulted in a pronounced delay in tumor growth. Building on this proof of concept, we have developed IRP2 inhibitors that significantly reduce IRP2 expression and hinder its interaction with iron-responsive elements in key iron-regulating proteins, such as ferritin heavy chain 1 (FTH1) and transferrin receptor (TFRC), culminating in iron depletion and a marked reduction in CRC cell proliferation. Furthermore, these inhibitors are shown to activate the AMPK-ULK1-Beclin1 signaling cascade, leading to cell death in CRC models.ConclusionsCollectively, these findings highlight the therapeutic potential of targeting IRP2 to exploit the disruption of iron metabolism in CRC, presenting a strategic advancement in addressing a critical area of unmet clinical need.

Critical success criteria for construction projects: a systematic literature evaluation

PurposeEvaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.Design/methodology/approachThe researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.FindingsUsing the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.Research limitations/implicationsConsidering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.Originality/valueThis study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

Strategic Advancements in Rice Cultivation: Combating Heat Stress through Genetic Innovation and Sustainable Practices—A Review

Strategic Advancements in Rice Cultivation: Combating Heat Stress through Genetic Innovation and Sustainable Practices—A Review

Research analytics capabilities (RAC) survey: development, validation and revision using the Rasch model

PurposeThe research enterprise within higher education is becoming more competitive as funding agencies require more collaborative research projects, higher-level of accountability and competition for limited resources. As a result, research analytics has emerged as a field, like many other areas within higher education to act as a data-informed unit to better understand how research institutions can effectively grow their research strategy. This is a new and emerging field within higher education.Design/methodology/approachAs businesses and other industries are embracing recent advances in data technologies such as cloud computing and big data analytic tools to inform decision making, research administration in higher education is seeing a potential in incorporating advanced data analytics to improve day-to-day operations and strategic advancement in institutional research. This paper documents the development of a survey measuring research administrators’ perspectives on how higher education and other research institutions perceive the use of data and analytics within the research administration functions. The survey development process started with composing a literature review on recent developments in data analytics within the research administration in the higher education domain, from which major components of data analytics in research administration were conceptualized and identified. This was followed by an item matrix mapping the evidence from literature with corresponding, newly drafted survey items. After revising the initial survey based on suggestions from a panel of subject matter experts to review, a pilot study was conducted using the revised survey instrument and validated by employing the Rasch measurement analysis.FindingsAfter revising the survey based on suggestions from the subject matter experts, a pilot study was conducted using the revised survey instrument. The resultant survey instrument consists of six dimensions and 36 survey items with an establishment of reasonable item fit, item separation and reliability. This survey protocol is useful for higher educational institutions to gauge research administrators’ perceptions of the culture of data analytics use in the workplace. Suggestions for future revisions and potential use of the survey were made.Originality/valueVery limited scholarly work has been published on this topic. The use of data-informed and data-driven approaches with in research strategy within higher education is an emerging field of study and practice.

Machine Learning Applications of Quantum Computing: A Review

At the intersection of quantum computing and machine learning, this review paper explores the transformative impact these technologies are having on the capabilities of data processing and analysis, far surpassing the bounds of traditional computational methods. Drawing upon an in-depth analysis of 32 seminal papers, this review delves into the interplay between quantum computing and machine learning, focusing on transcending the limitations of classical computing in advanced data processing and applications. This review emphasizes the potential of quantum-enhanced methods in enhancing cybersecurity, a critical sector that stands to benefit significantly from these advancements. The literature review, primarily leveraging Science Direct as an academic database, delves into the transformative effects of quantum technologies on machine learning, drawing insights from a diverse collection of studies and scholarly articles. While the focus is primarily on the growing significance of quantum computing in cybersecurity, the review also acknowledges the promising implications for other sectors as the field matures. Our systematic approach categorizes sources based on quantum machine learning algorithms, applications, challenges, and potential future developments, uncovering that quantum computing is increasingly being implemented in practical machine learning scenarios. The review highlights advancements in quantum-enhanced machine learning algorithms and their potential applications in sectors such as cybersecurity, emphasizing the need for industry-specific solutions while considering ethical and security concerns. By presenting an overview of the current state and projecting future directions, the paper sets a foundation for ongoing research and strategic advancement in quantum machine learning.

Strategic advancement of E3 ubiquitin ligase in the management of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) presents a significant global health challenge due to its high incidence, poor prognosis, and limited treatment options. As a pivotal regulator of protein stability, E3 ubiquitin ligase plays a crucial role in tumorigenesis and development. This review provides an overview of the latest research on the involvement of E3 ubiquitin ligase in hepatocellular carcinoma and elucidates its significance in hepatocellular carcinoma cell proliferation, invasion, and evasion from immune surveillance. Special attention is given to the functions of RING, HECT, and RBR E3 ubiquitin ligases and their association with hepatocellular carcinoma progression. By dissecting the molecular mechanisms and regulatory networks governed by E3 ubiquitin ligase, several potential therapeutic strategies are proposed: including the development of specific inhibitors targeting E3 ligases; augmentation of their tumor suppressor activity through drug or gene therapy; utilization of E3 ubiquitin ligase to modulate immune checkpoint proteins for improved efficacy of immunotherapy; combination strategies integrating traditional therapies with E3 ubiquitin ligase inhibitors; as well as biomarker development based on E3 ubiquitin ligase activity. Furthermore, this review discusses the prospect of overcoming drug resistance in hepatocellular carcinoma treatment through these novel approaches. Overall, this review establishes a theoretical foundation and offers fresh insights into harnessing the potential of E3 ubiquitin ligase for treating hepatocellular carcinoma while highlighting future research directions that pave the way for clinical translation studies and new drug discoveries.

Controlled dion-jacobson low-dimensional surface phase enables highly efficient and stable perovskite solar cells

The 2D/3D heterojunction structure emerges as a viable approach for enhancing the efficiency and stability of perovskite photovoltaics. However, the formation of an accumulative low-dimensional 2D perovskite (n=1) cladding layer often impedes carrier transport due to the insulating nature and high quantum confinement, and there is a paucity of detailed understanding regarding its surface phase control. This study introduces a Dion-Jacobson (DJ) phase 2D perovskite, employing decane-1,10-diammonium diiodide (DDADI) to interface with 3D perovskite, leveraging long-chain diammonium cations for structural stability and defect passivation on the 3D FAPbI3 perovskite surface. In addition, a novel PbI2-assisted phase control (PAPC) technique is proposed to mitigate the quantum confinement effects of the 2D layer, especially reducing the formation of the highly confined insulating n=1 phase. X-ray scattering analysis confirms the method's efficacy in promoting the formation of an n=2 phase, facilitating cascading HOMO levels and improving hole carrier transport. The optimized 2D/3D perovskite solar cell (PSC) achieve an exemplary efficiency of 25.16 %, with a notable open-circuit voltage of 1.192 V, and retain 92.9 % of its initial efficiency after 1000 hours in a nitrogen atmosphere, signifying a strategic advancement in 2D/3D PSC construction.