Frontiers in Biotechnology and Genetics is a peer-reviewed journal dedicated to publishing high-quality research in biotechnology and genetics. The journal seeks to bridge fundamental discoveries and real-world applications, providing a platform for scientists, researchers, and clinicians to share advances that drive the field forward. With an emphasis on interdisciplinary work, it covers a wide range of topics, including biological diagnostics, therapeutic development, biomedical devices, functional genomics, genetic variation, bioinformatics, synthetic biology, systems biology, and translational applications.
Computationally Driven Discovery of Novel p53 Y220C Stabilizers
The p53 Y220C mutation is a critical cancer‑driving factor, making the development of small‑molecule stabilizers capable of restoring its function an urgent clinical need. To accelerate the discovery of novel p53 Y220C stabilizers, this study employed an innovative computer‑aided drug design strategy. Using the highly active molecule Activator 7 as a template, we performed a systematic virtual screening of the Freedom Space compound library by leveraging the Scaffold Hopper module of InfiniSee software in combination with its three‑dimensional pharmacophore and shape features. The workflow adopted a multi‑stage filtering strategy: an initial rapid screening based on 3D shape and pharmacophore matching was followed by high‑precision molecular docking and binding free‑energy prediction using the crystal structure of the p53 Y220C–KG13 covalent complex as the receptor model.Through this rational design pipeline, a series of structurally novel hit compounds with favorable predicted binding profiles were successfully identified. Among them, Candidate 2 not only retained the hydrogen‑bond interaction between the template and the key residue Thr150 but also formed an additional hydrogen‑bond network with the mutation‑core residues Cys220 and Gly154 through its unique architecture, exhibiting higher predicted binding affinity and specificity. This compound, based on a novel scaffold, lays a foundation for the development of a new generation of proprietary p53 Y220C stabilizers.In summary, this study established an efficient computational screening methodology and discovered structurally novel potential p53 Y220C stabilizers, providing a critical starting point for subsequent experimental validation and lead‑compound optimization.
Copyright (c) 2026 Kang Wang, Xingyong Liu (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The regulatory role of the n-6/n-3 ratio in intestinal barrier function and glucose and lipid metabolism disorders
An unbalanced intake of n-6 and n-3 polyunsaturated fatty acids (PUFAs) can damage the gut barrier and disturb metabolism. This study used a high-fat diet mouse model of diabetes to examine the effects of different n-6/n-3 ratios (20:1, 10:1, and 4:1). Mice were fed the test diets for 12 weeks. When the ratio was reduced to 4:1, villus height and tight-junction protein levels increased by about 50%. Plasma lipopolysaccharide (LPS) dropped by 42%, and the HOMA-IR index decreased by 32%. The gut microbiota also changed, showing more Bifidobacterium and Bacteroides in the 4:1 group. These results indicate that a lower n-6/n-3 ratio supports the intestinal barrier, lowers endotoxin levels, and improves insulin sensitivity. The study suggests that keeping an n-6/n-3 ratio near 4:1 may help control inflammation and reduce metabolic problems linked to diabetes.
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
Privacy-Aware Clinical NLP with Differentially Private Fine-Tuning of Large Language Models
The integration of Large Language Models (LLMs) into clinical workflows promises to revolutionize medical informatics by automating tasks such as clinical note summarization, diagnostic coding, and patient triage. However, the deployment of these models is severely constrained by the sensitivity of clinical data and stringent regulatory frameworks regarding Protected Health Information (PHI). Standard de-identification techniques often fail to prevent memorization of training data, leaving models vulnerable to membership inference and reconstruction attacks. This paper presents a comprehensive framework for Privacy-Aware Clinical NLP, utilizing Differentially Private Fine-Tuning (DP-FT) on transformer-based architectures. We propose a hybrid approach that integrates Low-Rank Adaptation (LoRA) with Differentially Private Stochastic Gradient Descent (DP-SGD) to mitigate the computational overhead and utility degradation typically associated with private training. By injecting calibrated Gaussian noise into the gradient updates of low-rank adapters while keeping the pre-trained backbone frozen, we achieve a rigorous privacy guarantee without catastrophic forgetting. Our experimental results on the MIMIC-III and MIMIC-IV datasets demonstrate that our method retains high clinical utility in Named Entity Recognition (NER) and summarization tasks while satisfying strict differential privacy budgets (ε<3). This work bridges the gap between theoretical privacy guarantees and practical clinical utility, offering a viable path for the secure deployment of LLMs in healthcare environments.
Multi-Omics Integration via Variational Graph Autoencoders for Biomarker Discovery
The advent of high-throughput sequencing technologies has ushered in an era of multi-omics data availability, encompassing genomics, transcriptomics, epigenomics, and proteomics. While these diverse modalities offer complementary views of biological systems, integrating them to unravel complex disease mechanisms remains a significant computational challenge. Traditional integration methods often fail to capture the non-linear interactions and the underlying topological structure of biological networks. This paper proposes a novel framework utilizing Variational Graph Autoencoders (VGAE) for the robust integration of multi-omics data, specifically tailored for biomarker discovery in oncology. By constructing patient-similarity networks and leveraging the generative capabilities of variational inference, our approach effectively learns a low-dimensional latent representation that preserves both global graph structure and local feature attributes. We demonstrate that this method outperforms state-of-the-art matrix factorization and deep learning baselines in clustering accuracy and survival prediction. Furthermore, we introduce a gradient-based attribution mechanism to identify high-confidence biomarkers, validating their biological relevance against known pathway databases. Our results suggest that graph-based deep learning offers a scalable and mathematically rigorous path toward precision medicine.
Comprehensive Analysis Identified and Validated CX3CR1 as Potential Biomarkers for Atherosclerosis
Background: The etiology and disease development of atherosclerosis (AS) are still incompletely understood. In this research, we try to identify the gene biomarkers that play roles in the development and progression of AS and the relationship with immune cells. Methods: By mining Gene Expression Omnibus (GEO) database, we acquired the dataset of AS for further research. After identifying the differentially expressed genes (DEGs) shared by AS and normal control samples, we performed functional enrichment analysis to them. Integrating the least absolute shrinkage and selection operator (LASSO) algorithm, support vector machine recursive feature elimination (SVM-RFE) algorithm, and random forest (RF) algorithm we ultimately selected genes candidates for the development of AS. Using CIBERSORT method, the difference of the immune infiltration of AS and normal control samples were analyzed. We also investigate the correlation of optimal gene biomarkers and specific several types of immune cells. Results: DEGs were involved in the Toll-like receptor signaling pathways and Leukocyte transendothelial migration. Results of Gene Ontology (GO) analysis showed significant enrichment of DEGs in regulation of inflammatory response, leukocyte migration, and immune receptor activity. While Disease Ontology (DO) analysis indicated that DEGs are significantly enriched in terms including lung disease, atherosclerosis, coronary artery disease, and arteriosclerosis. CX3CR1 and C3 were screened by the LASSO, SVM-REF, and RF algorithms. AS samples showed relatively low infiltration levels of naive B cells (P<0.001), plasma cells (P<0.001), resting memory CD4 T cells (P<0.001), activated memory CD4 T cells (P<0.001), monocytes (P<0.001), M1 macrophages (P<0.001), M2 macrophages (P<0.001), activated dendritic cells (P=0.009), resting mast cells (P<0.001), and neutrophils (P=0.049) than normal controls, While AS samples harbored higher infiltration levels of memory B cells (P<0.001), follicular helper T cells(P<0.001), gamma delta T cells (P<0.001), M0 macrophages (P<0.001), and activated mast cells (P<0.001) compared with normal control samples. We also identified non-negligible links between the expression levels of CX3CR1 and immune cells including M0 macrophages and M1 macrophages. Conclusions: CX3CR1 played critical roles on the development of AS and had the potential as prognosis biomarkers for AS patients.
Copyright (c) 2025 Hongxuan Li, Xin Liu, Yanhui Cen, Wei Jia, Bojia Li, Xiaoying Qu, Qiyan Jin (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Airway mucus penetration and anti-inflammatory effects of charge-tunable nanocarriers in an asthma model
In asthma, thick airway mucus blocks drug movement and lowers treatment efficiency. In this study, lipid nanoparticles (LNPs) with different surface charges (+20 mV, 0 mV, and −20 mV) were made to test how charge affects mucus transport and anti-inflammatory action. The LNPs had an average size of 160 ± 12 nm and were studied in mice with ovalbumin (OVA)-induced asthma. Imaging results showed that neutral LNPs spread more evenly in the lungs and stayed for up to 8 hours, while positively and negatively charged ones cleared faster. Measurement of inflammation markers showed that the neutral group lowered IL-4 and IL-13 levels by about 65% (P < 0.001) compared with the positive group. These findings show that neutral charge helps nanoparticles pass through mucus, remain longer in the lungs, and produce stronger anti-inflammatory effects. This work provides a simple way to improve inhaled nanoparticle treatments for asthma and other airway diseases with mucus buildup.
Domain-Adaptive Knowledge-Enhanced Learning for Generalized Food Hazard Identification
The complexity of modern food safety monitoring systems demands sophisticated approaches that can effectively identify hazards across diverse food domains while adapting to evolving contamination patterns and analytical conditions. Traditional machine learning approaches often fail when confronted with domain shifts between different food categories, processing environments, or detection methodologies. This research presents a comprehensive domain-adaptive knowledge-enhanced learning framework specifically designed to address the fundamental challenges in generalized food hazard identification. Our approach builds upon extensive analysis of 114 machine learning studies in food safety applications, revealing critical patterns in algorithm selection and application domains that inform our architectural design decisions. The framework integrates domain-adversarial neural networks with gradient reversal mechanisms to learn domain-invariant feature representations while preserving hazard-discriminative information across multiple food domains. The core architecture employs a sophisticated three-component design consisting of a feature extractor that learns transferable representations, a label predictor optimized for hazard classification, and a domain classifier that enables adversarial training through gradient reversal techniques. Knowledge enhancement is achieved through integration of structured food safety expertise and ensemble learning approaches that combine multiple weak learners to achieve superior generalization performance. Comprehensive evaluation across biological hazards, chemical contaminants, and physical hazards demonstrates significant improvements over conventional approaches, with cross-domain accuracy gains of 14.8% and ensemble-enhanced performance achieving 91.3% accuracy across diverse food matrices. The framework successfully addresses the critical challenge of limited training data in emerging hazard detection scenarios, achieving 87.6% accuracy with minimal labeled examples through effective domain adaptation and knowledge transfer. Our approach provides interpretable predictions supported by domain expertise while maintaining computational efficiency suitable for real-time food safety monitoring applications. This work establishes a new paradigm for intelligent food safety systems that can adapt to evolving food environments and emerging contamination patterns without requiring extensive retraining.
Challenges and Opportunities for the Emerging Generation
The emerging generation faces a rapidly transforming world shaped by technological innovation, shifting socio-economic paradigms, and evolving cultural norms. This paper explores the duality of challenges and opportunities that characterize this transitional period, focusing on the interplay between globalization, digitalization, education, employment, and mental well-being. By examining the effects of rapid technological integration, climate change concerns, and shifting workforce demands, the study highlights strategies for harnessing opportunities while mitigating potential risks. The analysis suggests that adaptive learning, cross-cultural competency, and responsible innovation will play pivotal roles in enabling the emerging generation to navigate these complex landscapes.
Copyright (c) 2025 Dr. Amelia Thompson (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Innovations Shaping the Future Generation
The rapid pace of technological and societal change in the 21st century is redefining the opportunities, challenges, and skill requirements for the next generation. Innovations such as artificial intelligence, biotechnology, renewable energy solutions, and digital learning platforms are fundamentally altering the ways individuals interact, work, and learn. This article explores the transformative impact of these innovations on the future generation, analyzing their potential to drive socio-economic development, enhance global connectivity, and address pressing global issues. The discussion highlights both the opportunities and ethical challenges arising from these advancements, offering insights for policymakers, educators, and innovators.
Copyright (c) 2025 Dr. Sophia Martinez (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Bridging Generations Through Technology and Culture
In the contemporary era, technology and culture have emerged as twin pillars connecting different generations in unprecedented ways. While technology provides tools for real-time communication, collaborative creation, and knowledge sharing, culture offers the shared narratives, values, and traditions that anchor intergenerational understanding. This paper examines how these two forces converge to create inclusive spaces where generational gaps are minimized. Through an exploration of digital platforms, cultural preservation initiatives, and educational exchanges, the study highlights the potential of integrated approaches in fostering empathy, social cohesion, and cultural continuity. The discussion also identifies challenges, including digital literacy disparities and cultural homogenization, proposing strategic frameworks to ensure that technology enhances, rather than erodes, cultural diversity.
The Power of Ideas in the New Generation
Ideas have historically served as the foundation for transformative social, economic, and political change. In the context of the new generation, the velocity of idea formation, sharing, and implementation has accelerated due to globalization, technological innovation, and social connectivity. This paper explores how ideas shape identities, drive innovation, and redefine societal structures among the youth. By examining the interaction between creative thought, digital platforms, and collaborative cultures, this study highlights the role of ideas in fostering sustainable development, inclusive growth, and global cooperation. The findings suggest that empowering the new generation to develop and act upon impactful ideas is essential for shaping the future.
Copyright (c) 2025 Dr. Emily Carter (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Early Detection of Food Safety Hazards in Global Supply Chains Using Predictive Analytics
The globalization of food supply chains has introduced complex challenges for ensuring food safety across production, transport, and distribution systems. Delays in identifying contamination events can lead to large-scale public health crises and significant economic losses. This paper explores a predictive analytics framework for the early detection of food safety hazards within global supply chains. By integrating historical inspection data, environmental metrics, and transport conditions with machine learning algorithms, the system identifies high-risk nodes and anticipates potential outbreaks before they occur. Results demonstrate that the proposed model achieves high accuracy and lead time advantages in predicting microbial and chemical hazard risks. This approach provides actionable insights for regulators, manufacturers, and logistics providers, enabling timely interventions and enhancing consumer safety across borders.
The Intersection of Biotechnology and Genetics in Agricultural Biotechnology
The integration of biotechnology and genetics in agricultural biotechnology represents a transformative advancement in modern agriculture. This paper explores how the convergence of these fields has revolutionized crop production, pest management, and sustainability. Through genetic modification, gene editing technologies such as CRISPR, and biotechnological innovations, researchers have developed crops with enhanced traits, such as improved resistance to diseases, better nutritional profiles, and increased yields. This paper reviews the historical development, current applications, and future prospects of agricultural biotechnology. It also addresses the ethical, environmental, and economic implications of these technologies, providing a comprehensive overview of their impact on global agriculture.
Copyright (c) 2024 Frontiers in Biotechnology and Genetics
Biotechnology and Gene Therapy: Transforming the Treatment of Genetic Diseases
Gene therapy represents a revolutionary approach in biotechnology, aiming to address the root causes of genetic diseases through direct modification of the genome. This article explores the evolution of gene therapy, focusing on the latest advances in biotechnology that have significantly improved its efficacy and safety. We discuss various gene delivery methods, including viral and non-viral vectors, and highlight the applications of gene therapy in treating conditions such as cystic fibrosis, muscular dystrophy, and certain types of cancer. The review also covers ethical considerations, regulatory challenges, and future directions for the field. By examining the transformative potential of gene therapy, this article underscores its role in reshaping the landscape of genetic disease treatment.
The Evolution of Genetic Vaccines: From Concept to Clinical Applications
The field of genetic vaccines has evolved rapidly from theoretical concepts to practical clinical applications. This article provides a comprehensive review of the development of genetic vaccines, highlighting their transition from initial research to real-world use. Genetic vaccines, including DNA and mRNA vaccines, have shown significant promise in preventing and treating infectious diseases, cancers, and other conditions. This review discusses the historical development, technological advancements, and clinical applications of genetic vaccines, with a focus on recent successes such as COVID-19 mRNA vaccines. Challenges and future directions in the field are also explored, emphasizing the potential of genetic vaccines to revolutionize medicine.
Bioethical Considerations in Human Genetic Research and Biotechnology
Human genetic research and biotechnology have revolutionized medicine and agriculture, offering unprecedented opportunities to understand and manipulate genetic material. However, these advancements also raise significant bioethical concerns. This article explores the ethical implications of genetic research and biotechnology, including issues of consent, privacy, discrimination, and the potential for misuse of genetic information. By examining current ethical frameworks and guidelines, we aim to provide a comprehensive overview of the challenges and propose strategies for addressing these concerns in the context of ongoing scientific advancements.
Genetic Diversity in Biotechnology: Harnessing Variation for Improved Outcomes
Genetic diversity is a cornerstone of biotechnology, providing a vast reservoir of genetic material that can be harnessed to enhance various applications, from agriculture to medicine. This paper explores how genetic variation can be utilized to improve biotechnological outcomes. We examine the role of genetic diversity in crop improvement, livestock breeding, microbial applications, and human health. By leveraging diverse genetic resources, biotechnologists can develop more resilient crops, create effective therapies, and address global challenges such as food security and disease management. The paper also discusses the challenges and ethical considerations associated with exploiting genetic diversity, emphasizing the need for sustainable practices and equitable access to genetic resources.
The Role of Genomic Medicine in Cancer Treatment and Diagnosis
Genomic medicine has transformed cancer treatment and diagnosis by providing deeper insights into the genetic underpinnings of malignancies. This article explores the integration of genomic medicine into oncology, highlighting its impact on personalized treatment strategies, early diagnosis, and patient outcomes. By leveraging advances in genome sequencing, bioinformatics, and targeted therapies, genomic medicine enables more precise and individualized approaches to cancer care. The review discusses key developments, current applications, challenges, and future directions in the field, emphasizing the potential of genomic medicine to revolutionize cancer management.
Biotechnology in Environmental Conservation: Genetic Tools for Biodiversity Preservation
Biotechnology has emerged as a pivotal tool in environmental conservation, offering innovative genetic approaches to preserve biodiversity. This article explores the application of genetic tools in addressing challenges related to biodiversity loss, focusing on gene editing, genomic monitoring, and synthetic biology. By leveraging advances in biotechnology, conservationists can enhance species recovery, protect endangered ecosystems, and combat the impacts of climate change. This paper reviews current technologies, case studies, and future directions, emphasizing the role of biotechnology in promoting ecological sustainability and preserving genetic diversity.
Genomics and Bioinformatics: Integrating Data for Better Genetic Insights
Genomics and bioinformatics are pivotal in advancing our understanding of genetic data and its implications for health, agriculture, and disease. This article explores the integration of genomic data with bioinformatics tools to enhance the accuracy and depth of genetic insights. By examining the current methodologies, technologies, and applications, we highlight how the synergy between genomics and bioinformatics facilitates more robust analyses and innovative discoveries. The paper discusses key developments in sequencing technologies, data analysis frameworks, and the application of integrated data in personalized medicine, evolutionary studies, and agricultural genomics. Emphasis is placed on the challenges and future directions in the field to optimize the use of large-scale genomic data for practical applications.
The Impact of Synthetic Biology on Genetic Research and Biotechnology
Synthetic biology represents a transformative approach in genetic research and biotechnology, offering unprecedented opportunities to manipulate and engineer biological systems. This article explores the impact of synthetic biology on various facets of genetic research and biotechnology, including gene synthesis, metabolic engineering, and the development of novel therapeutic strategies. By examining key advancements, challenges, and future directions, this study highlights how synthetic biology is reshaping the landscape of biotechnology, with implications for medicine, agriculture, and environmental sustainability.
Biotechnological Approaches to Rare Genetic Disorders: Innovations and Challenges
Biotechnological approaches have significantly advanced the understanding and treatment of rare genetic disorders. These conditions, often characterized by their low prevalence and genetic underpinnings, pose unique challenges that require innovative solutions. Recent developments in gene therapy, genome editing, and personalized medicine have shown promising results in managing and potentially curing these disorders. This article reviews current biotechnological strategies, explores the associated challenges, and discusses future directions for research and application. Emphasis is placed on cutting-edge techniques, including CRISPR/Cas9, viral vector-based therapies, and innovative drug delivery systems. The article also addresses ethical, regulatory, and logistical considerations critical to advancing these therapies from the laboratory to clinical practice.
Genetic Modification of Microorganisms: Applications in Industry and Medicine
Genetic modification of microorganisms has revolutionized various industries and medical fields by enhancing microbial capabilities and enabling new applications. This article explores the advances in genetic engineering techniques used to modify microorganisms, focusing on their applications in industrial processes and medical treatments. By discussing key technologies such as CRISPR-Cas9 and plasmid-based systems, the article highlights how genetic modifications have led to improved production of pharmaceuticals, biofuels, and enzymes, as well as advancements in gene therapy and diagnostics. The paper also addresses the ethical and safety considerations associated with these modifications, offering a balanced view of their benefits and challenges.
Biotechnology in Agriculture: Enhancing Crop Yields and Sustainability
Biotechnology has emerged as a pivotal force in modern agriculture, offering innovative solutions to enhance crop yields and promote sustainability. This article explores the role of biotechnological advancements in agriculture, focusing on genetic engineering, plant tissue culture, and bioinformatics. By examining recent developments and case studies, it highlights how these technologies contribute to increased agricultural productivity, improved crop resistance to pests and diseases, and sustainable farming practices. The integration of biotechnology in agriculture not only addresses food security challenges but also supports environmental conservation through resource-efficient practices. The paper concludes with a discussion on future trends and the potential impact of biotechnological innovations on global agriculture.
Ethical Implications of Genetic Engineering: Balancing Innovation and Responsibility
Genetic engineering, a revolutionary technology with profound implications for medicine, agriculture, and industry, raises significant ethical questions. This paper explores the ethical dimensions of genetic engineering, focusing on the balance between innovation and responsibility. It examines the benefits of genetic modifications, such as disease prevention and agricultural enhancement, while addressing concerns related to safety, equity, and the potential for misuse. By reviewing existing frameworks and case studies, the paper aims to provide a balanced perspective on how to navigate the ethical challenges associated with genetic engineering and ensure responsible progress in this transformative field.
The Role of Biotechnology in Personalized Medicine: Current Trends and Future Directions
Personalized medicine represents a significant shift from traditional healthcare approaches, emphasizing the customization of medical treatment based on individual genetic, environmental, and lifestyle factors. Biotechnology plays a pivotal role in this transformation by providing advanced tools and techniques for understanding and manipulating genetic information. This article reviews current trends in biotechnology that are driving personalized medicine, including genomic sequencing, gene editing, and biomarkers. We also explore future directions, such as the integration of artificial intelligence, advancements in bioinformatics, and the challenges related to ethical and regulatory issues. The aim is to highlight how biotechnology is shaping personalized medicine and to discuss the potential impacts on healthcare delivery and patient outcomes.
Advancements in Gene Editing Technologies: From CRISPR to Beyond
Gene editing technologies have revolutionized the field of genetics, offering unprecedented precision in modifying DNA sequences. This article explores the evolution of gene editing technologies, focusing on CRISPR-Cas9, the most transformative advancement in recent years. It examines the fundamental mechanisms of CRISPR, its applications in research and medicine, and emerging alternatives and improvements. The review highlights the ethical, regulatory, and practical challenges associated with these technologies, providing a comprehensive overview of their current state and future prospects. By analyzing the trajectory of gene editing advancements, this article aims to provide insights into how these technologies are shaping the future of genetics and biotechnology.