Key Discoveries Research Articles

Microscopy methods for the in vivo study of nanoscale nuclear organization.

Eukaryotic genomes are highly compacted within the nucleus and organized into complex 3D structures across various genomic and physical scales. Organization within the nucleus plays a key role in gene regulation, both facilitating regulatory interactions to promote transcription while also enabling the silencing of other genes. Despite the functional importance of genome organization in determining cell identity and function, investigating nuclear organization across this wide range of physical scales has been challenging. Microscopy provides the opportunity for direct visualization of nuclear structures and has pioneered key discoveries in this field. Nonetheless, visualization of nanoscale structures within the nucleus, such as nucleosomes and chromatin loops, requires super-resolution imaging to go beyond the ~220 nm diffraction limit. Here, we review recent advances in imaging technology and their promise to uncover new insights into the organization of the nucleus at the nanoscale. We discuss different imaging modalities and how they have been applied to the nucleus, with a focus on super-resolution light microscopy and its application to in vivo systems. Finally, we conclude with our perspective on how continued technical innovations in super-resolution imaging in the nucleus will advance our understanding of genome structure and function.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review.

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.

Design-driven innovation in the public sector: insights from case studies of initiatives in Taiwan

ABSTRACT Contemporary public sectors face inefficiency, poor service quality, and limited innovation capacity. Existing solutions often lack flexibility, overlook organizational and human factors, and fail to address complex challenges. While Taiwan has successful design-driven public sector innovation cases, systematic analysis and implementation guidelines remain scarce. This study aims to analyse 6 cases from the Taiwan Design Research Institute using a framework covering ‘Background and Origins’, ‘Challenges and Difficulties’, ‘Key Breakthroughs’, and ‘Major Output Achievements’. It identifies key success factors, such as cross-department communication, collaborative design participation, and design capacity building, and proposes a six-step innovation process: 1) Understanding Challenges and Opportunities, 2) Cultivating an Innovative Culture, 3) Integrating Design Thinking, 4) Allocating Resources and Training, 5) Partner Collaboration, and 6) Continuous Evaluation. The study highlights implementation challenges like resource limitations, bureaucratic delays, and regulatory constraints while demonstrating how design-driven approaches enhance public service quality, efficiency, and responsiveness to citizen needs. This study demonstrates that design-driven innovation enhances public service quality, efficiency, and innovation. It aids officials in understanding citizen needs, aligning services with requirements, and providing systematic guidelines to address challenges, improve efficiency, and deliver better services in the public sector.

From bench to bedside: translational insights into aging research

Aging research has rapidly advanced from fundamental discoveries at the molecular and cellular levels to promising clinical applications. This review discusses the critical translational insights that bridge the gap between bench research and bedside applications, highlighting key discoveries in the mechanisms of aging, biomarkers, and therapeutic interventions. It underscores the importance of interdisciplinary approaches and collaboration among scientists, clinicians, and policymakers to address the complexities of aging and improve health span.

Bitcoin prediction with a hybrid model

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combina-tion of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The sec-ond key discovery was that a strong combination forecasting model that responds to the multiple fluctua-tions that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction accuracy criterion and matching curve-fitting in this work demonstrated that if the residuals of the revised model are white noise, the forecasts are unbiased. Future work investigating robust hybrid model forecasting using fuzzy neural networks would be very interesting.

Digital finance, institutional quality, and carbon dioxide emissions in Africa

ABSTRACT The impact of digital finance on carbon dioxide emissions has generated conflicting findings, with some studies suggesting emissions reduction while others point to the contrary. To gain clarity amidst this contradictory evidence, examining the moderating role of institutional quality is crucial. This research delved into the intricate relationship between digital finance, institutional quality, and CO2 emissions across 45 African countries from 2004 to 2021. By employing the dynamic system-generalized method of moment (sys-GMM) technique, the study revealed a positive relationship between digital finance and CO2 emissions. However, a key discovery emerged as the analysis considered the moderating role of institutional quality. The results highlighted the significant decrease in CO2 emissions that results from the interaction between institutional quality and digital finance. Furthermore, there is a critical point at which well-established institutions start to offset the environmental consequences associated with digital finance. The positive impact of digital finance on emissions is mitigated when institutions reach a certain threshold level of quality.

Trans-scale live-imaging of an E5.5 mouse embryo using incubator-type biaxial light-sheet microscopy.

During mouse embryonic development, the embryonic day (E) 5.5 stage represents a crucial period for the formation of the primitive body axis, where the symmetry breaking of cellular states influences the multicellular system. Elucidating the detailed mechanisms of this process necessitates a trans-layered dynamic observation of the embryo and all internal cells. In this report, we present our success in achieving in-toto single-cell observation in a whole hemisphere of an E5.5 embryo for 12 h, using a newly developed incubator-type biaxial light-sheet microscope. To achieve the success, we optimized our microscope system, including an incubator for culture stability, and refining the observation protocol to reduce phototoxicity. Our key discovery is that the scan speed during light-sheet formation plays a critical role in reducing phototoxicity, rather than the irradiation intensity or the interval time between frames. This innovative system not only enabled in-toto single-cell tracking but also led to the discovery of the abrupt shrinking of embryos whose contractile center was located at the extraembryonic ectoderm during monotonous growth up to the E6.5 stage.

AI and Machine Learning in The Cloud: This Involves Using AI and Machine Learning in Cloud Computing

Artificial intelligence (AI) and machine learning (ML) have emerged as disruptive technologies that are redefining cloud computing. The incorporation of AI and machine learning into cloud platforms improves productivity, scalability, and flexibility, allowing organizations to handle massive amounts of data and make intelligent choices in real time. This study investigates the symbiotic relationship between AI/ML and cloud computing, focusing on how cloud architecture provides the computational capacity needed for AI and ML models while AI improves cloud resource allocation. The article discusses key breakthroughs such as AI-driven automation in cloud operations, predictive analytics, and intelligent application deployment. The report emphasizes the democratization of AI capabilities via cloud services, which make them available to small and medium-sized organizations (SMEs) without requiring considerable infrastructure investment. It also investigates the security hurdles, ethical concerns, and compliance issues that come with data-intensive AI systems on the cloud. Real-world applications include AI-powered recommendation systems, fraud detection, and tailored consumer experiences, demonstrating the strength of this synergy. The report indicates that incorporating AI and ML into cloud computing is critical for expanding technological landscapes, driving creativity, and helping enterprises to remain competitive. However, addressing data privacy, ethical AI usage, and fair access to cloud-based AI resources are crucial for long-term progress. This study provides insights for researchers and practitioners on leveraging AI/ML in the cloud to meet evolving technological and business needs.

BRCA1 and BRCA2: from cancer susceptibility to synthetic lethality.

The discovery of BRCA1 and BRCA2 as tumor susceptibility genes and their role in genome maintenance has transformed our understanding of hereditary breast and ovarian cancer. This review traces the evolution of BRCA1/2 research over the past 30 years, highlighting key discoveries in the field and their contributions to tumor development. Additionally, we discuss current preventive measures for BRCA1/2 mutation carriers and targeted treatment options based on the concept of synthetic lethality. Finally, we explore the challenges of acquired therapy resistance and discuss potential alternative avenues for targeting BRCA1/2 mutant tumors.

HIV capsids: orchestrators of innate immune evasion, pathogenesis and pandemicity.

Human immunodeficiency virus (HIV) is an exemplar virus, still the most studied and best understood and a model for mechanisms of viral replication, immune evasion and pathogenesis. In this review, we consider the earliest stages of HIV infection from transport of the virion contents through the cytoplasm to integration of the viral genome into host chromatin. We present a holistic model for the virus-host interaction during this pivotal stage of infection. Central to this process is the HIV capsid. The last 10 years have seen a transformation in the way we understand HIV capsid structure and function. We review key discoveries and present our latest thoughts on the capsid as a dynamic regulator of innate immune evasion and chromatin targeting. We also consider the accessory proteins Vpr and Vpx because they are incorporated into particles where they collaborate with capsids to manipulate defensive cellular responses to infection. We argue that effective regulation of capsid uncoating and evasion of innate immunity define pandemic potential and viral pathogenesis, and we review how comparison of different HIV lineages can reveal what makes pandemic lentiviruses special.

Mammary Cancer Models: An Overview from the Past to the Future.

Breast cancer research heavily relies on diverse model systems to comprehend disease progression, develop novel diagnostics, and evaluate new therapeutic strategies. This review offers a comprehensive overview of mammary cancer models, covering both ex vivo and in vivo approaches. We delve into established techniques, such as cell culture and explore cutting-edge advancements, like tumor-on-a-chip and bioprinting. The in vivo section encompasses spontaneous, induced, and transplanted models, genetically engineered models, chick chorioallantoic membrane assays, and the burgeoning field of in silico models. Additionally, this article briefly highlights the key discoveries made using these models, significantly enhancing our understanding of breast cancer. In essence, this article serves as a comprehensive compass, charting the trajectory of mammary cancer modeling from its early beginnings to the promising vistas of tomorrow.

Literasi Digital dan Etika Komunikasi dalam Konteks Media Sosial

Social media has emerged as a contemporary digital phenomenon that transforms the paradigm of communication and social interaction. This research aims to explore the complexity of social media from technological, social, and ethical perspectives. Utilizing a mixed-methods approach with a descriptive-exploratory design, the study analyzes data from the 2024 APJII survey and various documentary sources. Research findings demonstrate that social media possesses unique characteristics: participatory, open, and interconnected, which facilitate cross-geographical interaction. Key discoveries reveal that 40% of the Indonesian population are active social media users, with platforms such as Facebook and WhatsApp dominating the landscape. The research identifies positive and negative impacts of social media usage, including global connectivity opportunities and digital bullying risks. Approximately 49% of users have experienced cyberbullying, signaling the complexity of digital ethics. The study emphasizes the importance of digital literacy, critical awareness, and collective responsibility in managing cyber spaces. Research implications suggest the necessity of a holistic approach in understanding and regulating digital interactions, considering social, technological, and ethical dimensions.

Revolutionizing Financial Health Predictions: The Integration of GenAI and Advanced Machine Learning Techniques

Integrating Generative AI (GenAI) and advanced machine learning techniques into financial health predictions represents a revolutionary approach to financial technology. While prior research has incorporated machine learning and artificial intelligence into financial analysis, GenAI has not yet been incorporated into financial models. Our comprehensive experimental study aims to bridge this gap by harnessing the advanced capabilities of Generative AI to improve predictive accuracy and model robustness. The distinctive contribution of this study lies in its utilization of Generative AI, which offers novel insights and methodologies that traditional machine-learning techniques do not provide. A key discovery of this study is the alignment of Generative AI with quantitative models, revealing the potential to identify fraud and financial difficulties that stakeholders should consider before making investment decisions. Moreover, the study proposes that a mixed-method approach could be beneficial for future research in risk measurement. These unique and novel findings highlight that traditional methods would not have been able to uncover such insights. This research provides robust and interpretable financial assessments and contributes valuable knowledge to financial technology, showcasing the innovative application of Generative AI in financial health predictions.

Hypercoagubility: An Updated Overview for Healthcare Providers

Background: Hypercoagulability, or thrombophilia, is a pathological state characterized by an increased tendency for blood clot formation, leading to conditions such as venous thromboembolism (VTE), arterial thrombosis, and thromboembolism. This condition arises from a disruption in the balance between pro-coagulant and anticoagulant factors, influenced by both inherited and acquired risk factors. The understanding of hypercoagulability has evolved significantly since the early 20th century, with key discoveries such as antiphospholipid syndrome, factor V Leiden mutation, and deficiencies in proteins C and S contributing to improved diagnosis and management. Aim: This article aims to provide healthcare providers with an updated overview of hypercoagulability, including its etiology, epidemiology, pathophysiology, diagnostic approaches, and management strategies, to enhance the prevention and treatment of thrombotic disorders. Methods: The review synthesizes current literature on hypercoagulability, focusing on the interplay between genetic and environmental factors, the role of Virchow’s triad in thrombosis, and the clinical significance of various thrombophilic disorders. Diagnostic tools, risk assessment models, and treatment options, including anticoagulation therapy, are discussed in detail. Results: Hypercoagulability disorders are influenced by both inherited mutations (e.g., factor V Leiden, prothrombin G20210A) and acquired conditions (e.g., malignancy, inflammation, pregnancy). Thrombosis risk is further modulated by factors such as age, lifestyle, and comorbidities. Diagnostic approaches include thrombophilia screening and risk stratification tools, while management involves anticoagulation therapy tailored to individual patient risk profiles. Conclusion: Hypercoagulability is a multifactorial condition requiring a comprehensive understanding of its underlying causes and risk factors. Early diagnosis, risk stratification, and personalized treatment are essential to reduce morbidity and mortality associated with thrombotic disorders. Future research should focus on novel therapies and improved risk prediction models

Nanotechnology Therapy for Type 2 Diabetic Mellitus: Challenges and Future Perspectives

Nanotechnology, the study and the use of materials and systems in the nanoscale (1–100 nm) has transformed a number of industries, including healthcare. Nanoscience examines structures on this scale, and Nanotechnology applies these nanoscale structures to practical uses. Nanotechnology has ancient roots, with early civilizations unknowingly applying nanoscience principles in metallurgy, textile production, and art. However, modern nanotechnology emerged in the 20th century, gaining momentum through key discoveries, government programs, and global research initiatives. Nanotechnology has made major strides in the diagnosis and treatment of Type 2 Diabetes Mellitus (T2DM), providing innovative solutions such as drug delivery nanoparticles and accurate glucose monitoring nano sensors. Despite these developments, a number of issues with nanotechnology still need to be resolved before it can be widely used to treat type 2 diabetes. These issues include safety concerns, biological consequences, immunological reactions, and regulatory barriers. Future developments in artificial pancreas systems and tailored nanomedicine have enormous potential to enhance patient outcomes. Future developments could completely transform the management of type 2 diabetes by customizing medications to meet the needs of each patient and utilizing nanotechnology to improve drug targeting and glucose regulation.

Phosphoinositide signaling in the nucleus: Impacts on chromatin and transcription regulation.

Phosphoinositides also called Polyphosphoinositides (PPIns) are small lipid messengers with established key roles in organelle trafficking and cell signaling in response to physiological and environmental inputs. Besides their well-described functions in the cytoplasm, accumulating evidences pointed to PPIns involvement in transcription and chromatin regulation. Through the description of previous and recent advances of PPIns implication in transcription, this review highlights key discoveries on how PPIns modulate nuclear factors activity and might impact chromatin to modify gene expression. Finally, we discuss how PPIns nuclear and cytosolic metabolisms work jointly in orchestrating key transduction cascades that end in the nucleus to modulate gene expression.

A proteome-wide yeast degron collection for the dynamic study of protein function.

Genome-wide collections of yeast strains, known as libraries, revolutionized the way systematic studies are carried out. Specifically, libraries that involve a cellular perturbation, such as the deletion collection, have facilitated key biological discoveries. However, short-term rewiring and long-term accumulation of suppressor mutations often obscure the functional consequences of such perturbations. We present the AID library which supplies "on demand" protein depletion to overcome these limitations. Here, each protein is tagged with a green fluorescent protein (GFP) and an auxin-inducible degron (AID), enabling rapid protein depletion that can be quantified systematically using the GFP element. We characterized the degradation response of all strains and demonstrated its utility by revisiting seminal yeast screens for genes involved in cell cycle progression as well as mitochondrial distribution and morphology. In addition to recapitulating known phenotypes, we also uncovered proteins with previously unrecognized roles in these central processes. Hence, our tool expands our knowledge of cellular biology and physiology by enabling access to phenotypes that are central to cellular physiology and therefore rapidly equilibrated.

The history of cryotechnologies in reproductive medicine: From randomness to stability

The article provides an overview of the historical milestones in cryobiology, a scientific field that has found widespread practical application in reproductive medicine. Cryotechnologies have revolutionized assisted reproductive technologies, offering invaluable tools for the storage, protection, and management of reproductive cells such as sperm, oocytes, and embryos. The technology began with the first successful attempts at sperm cryopreservation, which not only demonstrated the possibility of preserving male gametes but also inspired a wave of research aimed at developing cryopreservation protocols for more sensitive and complex biological entities, including oocytes and preimplantation embryos. Cryopreservation has become a crucial component of fertility preservation, offering new opportunities for individuals and couples facing medical treatments that could compromise their reproductive potential, as well as providing options for delaying parenthood. Given the critical role of cryotechnologies in modern reproductive medicine, this article delves into the historical context of these developments, exploring the key breakthroughs that have shaped this field. The authors conducted an in-depth analysis of existing literature, drawing on a wide range of scientific databases to highlight the global impact of cryobiology on the current successes in reproductive medicine. Furthermore, the article presents the results of the authors' own research and practical experience in the field of reproductive cryobiology, with a particular focus on the application of these technologies in Ukraine. The review underscores the challenges and opportunities that have emerged throughout the history of cryopreservation, as well as ongoing efforts to improve and optimize these methods to further enhance infertility treatment outcomes. The discussion also addresses ethical and logistical considerations related to cryopreservation, particularly in the context of long-term storage and future use of cryopreserved materials. As cryobiology continues to evolve, its integration into reproductive medicine will undoubtedly lead to further innovations, making it a cornerstone of infertility treatment and reproductive health worldwide.

A Brief History of Cell Culture: From Harrison to Organs-on-a-Chip.

This comprehensive overview of the historical milestones in cell culture underscores key breakthroughs that have shaped the field over time. It begins with Wilhelm Roux's seminal experiments in the 1880s, followed by the pioneering efforts of Ross Granville Harrison, who initiated groundbreaking experiments that fundamentally shaped the landscape of cell culture in the early 20th century. Carrel's influential contributions, notably the immortalization of chicken heart cells, have marked a significant advancement in cell culture techniques. Subsequently, Johannes Holtfreter, Aron Moscona, and Joseph Leighton introduced methodological innovations in three-dimensional (3D) cell culture, initiated by Alexis Carrel, laying the groundwork for future consolidation and expansion of the use of 3D cell culture in different areas of biomedical sciences. The advent of induced pluripotent stem cells by Takahashi and Yamanaka in 2006 was revolutionary, enabling the reprogramming of differentiated cells into a pluripotent state. Since then, recent innovations have included spheroids, organoids, and organ-on-a-chip technologies, aiming to mimic the structure and function of tissues and organs in vitro, pushing the boundaries of biological modeling and disease understanding. In this review, we overview the history of cell culture shedding light on the main discoveries, pitfalls and hurdles that were overcome during the transition from 2D to 3D cell culture techniques. Finally, we discussed the future directions for cell culture research that may accelerate the development of more effective and personalized treatments.

Synthetic Data for Object Detection with Neural Networks: State-of-the-Art Survey of Domain Randomisation Techniques

Machine learning relies heavily on access to large and well-maintained datasets. In this article, we focus on Computer Vision and object detection applications to survey past research on automatic generation of annotated datasets that does not require costly and time-consuming human labelling. In specific, we analyse research done in the area of Domain Randomisation applied to Neural Networks predominant in object detection since the last decade. We propose a set of criteria for comparison of previously published works, and utilise these criteria to make conclusions about various trends in the area, similarities/differences and key discoveries made since conception. The purpose of this work is to advise practitioner on leading solutions and help researchers gain better understanding of the landscape. The key takeaways from our analysis show the current state-of-the-art solutions within the mid-quartile range allow object detection with typically about 1%–25% performance decrease in comparison to manually annotated datasets; while the top performant approaches above the upper quartile gain about 2%–32% lead over real data training in their specific application areas. Our survey shows the future outlook is more research into 3D generation techniques, with most innovative yet complex techniques related to end-to-end modifications of entire network architectures to suit synthetic data training.