Frontiers in Biotechnology and Genetics
type: channel
description: 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.
publisher: INTERNATIONAL STUDY COUNSELOR
language: en
publication name: Frontiers in Biotechnology and Genetics
issn: 3079-6709
items: Research Progress on Modeling Methods of TCM Syndromes in Experimental Animals
items: Research Progress in the Treatment of Hepatocellular Carcinoma via the PI3K/AKT Signaling Pathway
items: Disparities Between Treatment Need and Utilization for Substance Use Disorders in the United States A Population-Level Decomposition Analysis
items: Multi-Scale Assessment of Methanol Synthesis on ZrO2-on-Cu Inverse Catalysts
items: Deep Reinforcement Learning for Closed-Loop STN Brain Stimulation in Parkinson's and Circuit Mechanisms
items: Computationally Driven Discovery of Novel p53 Y220C Stabilizers
items: The regulatory role of the n-6/n-3 ratio in intestinal barrier function and glucose and lipid metabolism disorders
items: Privacy-Aware Clinical NLP with Differentially Private Fine-Tuning of Large Language Models
items: Multi-Omics Integration via Variational Graph Autoencoders for Biomarker Discovery
items: Comprehensive Analysis Identified and Validated CX3CR1 as Potential Biomarkers for Atherosclerosis
items: Airway mucus penetration and anti-inflammatory effects of charge-tunable nanocarriers in an asthma model
items: Domain-Adaptive Knowledge-Enhanced Learning for Generalized Food Hazard Identification
items: Challenges and Opportunities for the Emerging Generation
items: Innovations Shaping the Future Generation
items: Bridging Generations Through Technology and Culture
items: The Power of Ideas in the New Generation
items: Early Detection of Food Safety Hazards in Global Supply Chains Using Predictive Analytics
items: The Intersection of Biotechnology and Genetics in Agricultural Biotechnology
items: Biotechnology and Gene Therapy: Transforming the Treatment of Genetic Diseases
items: The Evolution of Genetic Vaccines: From Concept to Clinical Applications
items: Bioethical Considerations in Human Genetic Research and Biotechnology
items: Genetic Diversity in Biotechnology: Harnessing Variation for Improved Outcomes
items: The Role of Genomic Medicine in Cancer Treatment and Diagnosis
items: Biotechnology in Environmental Conservation: Genetic Tools for Biodiversity Preservation
items: Genomics and Bioinformatics: Integrating Data for Better Genetic Insights
items: The Impact of Synthetic Biology on Genetic Research and Biotechnology
items: Biotechnological Approaches to Rare Genetic Disorders: Innovations and Challenges
items: Genetic Modification of Microorganisms: Applications in Industry and Medicine
items: Biotechnology in Agriculture: Enhancing Crop Yields and Sustainability
items: Ethical Implications of Genetic Engineering: Balancing Innovation and Responsibility

Research Progress on Modeling Methods of TCM Syndromes in Experimental Animals
type: item
description: TCM syndrome is the core of TCM treatment based on syndrome differentiation. Modeling of TCM syndromes in experimental animals is an important bridge connecting TCM basic theory and modern medical research, and also a key technical support for carrying out TCM efficacy evaluation, pathogenesis exploration, and new drug research and development. With the continuous advancement of TCM modernization, the modeling technology of TCM syndromes in experimental animals has been gradually improved, and the modeling methods have shown a trend of diversification, standardization and refinement. This article systematically sorts out the basic principles and core modeling methods of TCM syndrome modeling in experimental animals, focuses on reviewing the specific modeling technologies, application status and research hotspots of common clinical TCM syndromes (such as qi deficiency syndrome, blood deficiency syndrome, yin deficiency syndrome, yang deficiency syndrome, phlegm-dampness syndrome, blood stasis syndrome, etc.), analyzes the existing problems in the current modeling process (such as inconsistent modeling standards, insufficient syndrome stability, imperfect evaluation system, etc.), and looks forward to the development direction of modeling technology in the future, so as to provide a reference for the standardized application of experimental animal syndrome modeling in TCM basic research.
subject: Articles
  topic: section
subject: Experimental animals
  topic: keywords
subject: TCM syndromes
  topic: keywords
subject: Modeling methods
  topic: keywords
subject: Research progress
  topic: keywords
subject: TCM modernization
  topic: keywords
creator: Zhuolin Zhang
creator: Zheyi Xu
creator: Huiying Teng
creator: Xiaona Li
creator: Jiaxin Tang
creator: Yanping Xu
creator: Hongxuan Li
creator: Xin Liu
rights: Copyright (c) 2026 Zhuolin Zhang, Zheyi Xu, Huiying Teng, Xiaona Li, Jiaxin Tang, Yanping Xu, Hongxuan Li, Xin Liu (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-03-25
publication date: 2026-03-25
starting page: 51
ending page: 70
doi: 10.71465/fbg752

Research Progress in the Treatment of Hepatocellular Carcinoma via the PI3K/AKT Signaling Pathway
type: item
description: The phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway is one of the core pathways regulating cell proliferation, survival and metabolism, and its aberrant activation is closely associated with the malignant progression of various cancers. This pathway consists of a cascade reaction of phosphatidylinositol 3-kinase (PI3K) and protein kinase B (AKT). In hepatocellular carcinoma (HCC), breast cancer and other tumors, this pathway is frequently constitutively activated due to the deletion of the PTEN tumor suppressor gene, mutation of the PIK3CA gene or overactivation of receptors, leading to malignant cell proliferation and chemoresistance. This paper reviews the research progress in the treatment of HCC targeting the PI3K/AKT signaling pathway, aiming to provide a reference for the basic research and clinical application of HCC therapy.
subject: Articles
  topic: section
subject: Hepatocellular carcinoma
  topic: keywords
subject: PI3K/AKT pathway
  topic: keywords
subject: Targeted therapy
  topic: keywords
subject: Drug resistance mechanism
  topic: keywords
subject: Combination therapy
  topic: keywords
creator: Xiaona Li
creator: Huiying Teng
creator: Jiaxin Tang
creator: Yanping Xu
creator: Hongxuan Li
creator: Zheyi Xu
creator: Xin Liu
rights: Copyright (c) 2026 Xiaona Li, Huiying Teng, Jiaxin Tang, Yanping Xu, Hongxuan Li, Zheyi Xu, Xin Liu (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-03-25
publication date: 2026-03-25
starting page: 39
ending page: 50
doi: 10.71465/fbg751

Disparities Between Treatment Need and Utilization for Substance Use Disorders in the United States A Population-Level Decomposition Analysis
type: item
description: Substance use disorders (SUDs) represent a persistent public health challenge in the United States, yet gaps remain between population-level treatment need and actual service utilization. This study examined temporal trends and structural disparities in SUD treatment need and receipt from 2012 to 2023 using nationally representative survey data from 412,836 adults. Treatment need was defined based on DSM-aligned diagnostic criteria, while treatment receipt was identified through self-reported engagement with specialty or non-specialty SUD services within the past year. Weighted prevalence estimates and age-standardized rates were calculated annually. A multivariable decomposition approach was applied to quantify the relative contributions of demographic, socioeconomic, insurance, and geographic factors to observed treatment gaps. Over the study period, the estimated prevalence of treatment need increased from 8.1% to 10.6%, while treatment receipt rose modestly from 12.4% to 15.8% among those in need. Decomposition analysis indicated that insurance coverage expansion accounted for 29.3% of the increase in treatment utilization, whereas income instability and rural residence contributed to 34.7% of the persistent unmet need. Younger adults aged 18–25 exhibited the largest absolute treatment gap, with only 18.2% receiving care despite meeting diagnostic criteria. These findings highlight that recent improvements in treatment access have been uneven and insufficient to offset rising need, underscoring the importance of structural and policy-level interventions to reduce persistent disparities in SUD care delivery.
subject: Articles
  topic: section
subject: Substance use disorders
  topic: keywords
subject: treatment utilization
  topic: keywords
subject: unmet treatment need
  topic: keywords
subject: health disparities
  topic: keywords
subject: population health
  topic: keywords
subject: decomposition analysis
  topic: keywords
creator: Daniel R. Hughes
creator: Charlotte M. Walker
creator: Emily J. Thompson
rights: Copyright (c) 2026 Daniel R. Hughes, Charlotte M. Walker, Emily J. Thompson (Author) https://creativecommons.org/licenses/by/4.0
date: 2026-03-01
publication date: 2026-03-01
starting page: 30
ending page: 38
doi: 10.71465/fbg725

Multi-Scale Assessment of Methanol Synthesis on ZrO2-on-Cu Inverse Catalysts
type: item
description: Bridging atomistic insights with reactor-level performance is essential for catalyst evaluation. In this study, a multi-scale framework integrating DFT calculations, microkinetic modeling, and plug-flow reactor simulations was developed for ZrO2-on-Cu inverse catalysts. The model predicts methanol space–time yields of 0.60–0.65 g g⁻¹ h⁻¹ under industrial conditions. Interface site density emerges as the dominant descriptor controlling productivity, outweighing surface area effects. The approach provides a quantitative link between interface chemistry and macroscopic performance.
subject: Articles
  topic: section
subject: multi-scale modeling
  topic: keywords
subject: inverse catalyst
  topic: keywords
subject: ZrO2/Cu
  topic: keywords
subject: methanol synthesis
  topic: keywords
subject: CO2 hydrogenation
  topic: keywords
creator: James A. Whitmore
creator: Emily R. Collins
creator: Daniel T. Harrington
rights: Copyright (c) 2026 James A. Whitmore, Emily R. Collins, Daniel T. Harrington (Author) https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2026-02-15
publication date: 2026-02-15
starting page: 21
ending page: 29
doi: 10.71465/fbg703

Deep Reinforcement Learning for Closed-Loop STN Brain Stimulation in Parkinson's and Circuit Mechanisms
type: item
description: Parkinson's disease represents a debilitating neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta, leading to pathological oscillatory synchronization within the basal ganglia-thalamocortical network. Deep Brain Stimulation of the Subthalamic Nucleus is a well-established symptomatic treatment; however, conventional continuous stimulation approaches often result in suboptimal clinical outcomes and adverse side effects due to their open-loop nature. This paper presents a comprehensive investigation into the application of Deep Reinforcement Learning for developing closed-loop, adaptive stimulation protocols. By formulating the neural modulation problem as a Markov Decision Process, we employ a deep neural network agent to learn optimal stimulation strategies that minimize pathological beta-band oscillations while optimizing energy consumption. Our computational approach utilizes a biophysically plausible mean-field model of the basal ganglia to simulate the complex circuit mechanisms underlying Parkinsonian states. The results demonstrate that the reinforcement learning agent successfully identifies non-linear control policies that outperform traditional proportional-integral-derivative controllers and continuous stimulation paradigms. Furthermore, the agent exhibits the capacity to adapt to biological variability and signal noise, suggesting a robust pathway toward patient-specific neuroprosthetics. This study elucidates the intersection of computational intelligence and neural circuit dynamics, offering a promising trajectory for the next generation of precision neuromodulation therapies.
subject: Articles
  topic: section
subject: Deep Brain Stimulation
  topic: keywords
subject: Reinforcement Learning
  topic: keywords
subject: Parkinson's Disease
  topic: keywords
subject: Subthalamic Nucleus.
  topic: keywords
creator: Julia Schmidt
creator: Lucia Fernandez
creator: Aditya Kumar
creator: Yusuf Ahmed
rights: Copyright (c) 2026 Julia Schmidt, Lucia Fernandez, Aditya Kumar, Yusuf Ahmed (Author) https://creativecommons.org/licenses/by-sa/4.0
date: 2026-02-25
publication date: 2026-02-25
starting page: 13
ending page: 20
doi: 10.71465/fbg679

Computationally Driven Discovery of Novel p53 Y220C Stabilizers
type: item
description: 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.
subject: Articles
  topic: section
subject: p53 Y220C
  topic: keywords
subject: Computer-Aided Drug Design
  topic: keywords
subject: Virtual Screening
  topic: keywords
subject: Scaffold Hopping
  topic: keywords
creator: Kang Wang
creator: Xingyong Liu
rights: Copyright (c) 2026 Kang Wang, Xingyong Liu (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-01-22
publication date: 2026-01-22
doi: 10.71465/fbg586

The regulatory role of the n-6/n-3 ratio in intestinal barrier function and glucose and lipid metabolism disorders
type: item
description: 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.
subject: Articles
  topic: section
subject: n-6/n-3 ratio
  topic: keywords
subject: gut barrier
  topic: keywords
subject: lipopolysaccharide
  topic: keywords
subject: tight-junction proteins
  topic: keywords
subject: insulin resistance
  topic: keywords
subject: gut microbiota
  topic: keywords
creator: Luca Moretti
creator: Anna Kovács
creator: Erik M. Lindberg
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-30
publication date: 2025-12-30
starting page: 69
ending page: 76
doi: 10.71465/fbg564

Privacy-Aware Clinical NLP with Differentially Private Fine-Tuning of Large Language Models
type: item
description: 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.
subject: Articles
  topic: section
subject: Differential Privacy
  topic: keywords
subject: Clinical NLP
  topic: keywords
subject: Large Language Models
  topic: keywords
subject: Parameter-Efficient Fine-Tuning
  topic: keywords
creator: Susan Lopez
creator: Joseph Hill
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-30
publication date: 2025-12-30
starting page: 61
ending page: 68
doi: 10.71465/fbg549

Multi-Omics Integration via Variational Graph Autoencoders for Biomarker Discovery
type: item
description: 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.
subject: Articles
  topic: section
subject: Multi-Omics Integration
  topic: keywords
subject: Variational Graph Autoencoders
  topic: keywords
subject: Biomarker Discovery
  topic: keywords
subject: Computational Biology
  topic: keywords
subject: Deep Learning
  topic: keywords
creator: Bo Peng
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-30
publication date: 2025-12-30
starting page: 51
ending page: 60
doi: 10.71465/fbg548

Comprehensive Analysis Identified and Validated CX3CR1 as Potential Biomarkers for Atherosclerosis
type: item
description: 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), follicul…
subject: Articles
  topic: section
subject: Atherosclerosis
  topic: keywords
subject: Biomarkers
  topic: keywords
subject: GEO
  topic: keywords
subject: Random Forest
  topic: keywords
subject: SVM-REF
  topic: keywords
subject: LASSO
  topic: keywords
creator: Hongxuan Li
creator: Xin Liu
creator: Yanhui Cen
creator: Wei Jia
creator: Bojia Li
creator: Xiaoying Qu
creator: Qiyan Jin
rights: 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
date: 2025-12-11
publication date: 2025-12-11
starting page: 51
ending page: 78
doi: 10.71465/

Airway mucus penetration and anti-inflammatory effects of charge-tunable nanocarriers in an asthma model
type: item
description: 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.
subject: Articles
  topic: section
subject: surface charge
  topic: keywords
subject: lipid nanoparticles
  topic: keywords
subject: asthma
  topic: keywords
subject: mucus transport
  topic: keywords
subject: lung delivery
  topic: keywords
subject: inflammation control
  topic: keywords
subject: nanoparticle therapy
  topic: keywords
creator: Liam A. McKenzie
creator: Gabriel Roy
creator: Amelia J. Leblanc
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: 45
ending page: 50
doi: 10.71465/fbg447

Domain-Adaptive Knowledge-Enhanced Learning for Generalized Food Hazard Identification
type: item
description: 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% accura…
subject: Articles
  topic: section
subject: domain adaptation
  topic: keywords
subject: food safety monitoring
  topic: keywords
subject: gradient reversal networks
  topic: keywords
subject: ensemble learning
  topic: keywords
subject: hazard identification
  topic: keywords
subject: knowledge enhancement
  topic: keywords
subject: machine learning classification
  topic: keywords
creator: Noah Ramirez
creator: Huilan Liu
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 29
ending page: 44
doi: 10.71465/fbg368

Challenges and Opportunities for the Emerging Generation
type: item
description: 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.
subject: Articles
  topic: section
subject: technological adaptation
  topic: keywords
subject: youth empowerment
  topic: keywords
subject: globalization
  topic: keywords
subject: digital economy
  topic: keywords
creator: Dr. Amelia Thompson
rights: Copyright (c) 2025 Dr. Amelia Thompson (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 23
ending page: 28
doi: 10.71465/fbg297

Innovations Shaping the Future Generation
type: item
description: 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.
subject: Articles
  topic: section
subject: innovation
  topic: keywords
subject: future generation
  topic: keywords
subject: technology
  topic: keywords
subject: societal change
  topic: keywords
creator: Dr. Sophia Martinez
rights: Copyright (c) 2025 Dr. Sophia Martinez (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 18
ending page: 22
doi: 10.71465/fbg296

Bridging Generations Through Technology and Culture
type: item
description: 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.
subject: Articles
  topic: section
subject: Intergenerational communication
  topic: keywords
subject: cultural preservation
  topic: keywords
subject: digital literacy
  topic: keywords
subject: technological innovation
  topic: keywords
creator: Dr. Amelia Thompson
rights: Copyright (c) 2025 Dr. Amelia Thompson (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 14
ending page: 17
doi: 10.71465/fbg294

The Power of Ideas in the New Generation
type: item
description: 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.
subject: Articles
  topic: section
subject: youth empowerment
  topic: keywords
subject: innovation
  topic: keywords
subject: globalization
  topic: keywords
subject: social change
  topic: keywords
subject: digital platforms
  topic: keywords
creator: Dr. Emily Carter
rights: Copyright (c) 2025 Dr. Emily Carter (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 9
ending page: 13
doi: 10.71465/fbg138

Early Detection of Food Safety Hazards in Global Supply Chains Using Predictive Analytics
type: item
description: 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.
subject: Articles
  topic: section
subject: Food Safety
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Global Supply Chains
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Hazard Detection
  topic: keywords
subject: Risk Forecasting
  topic: keywords
subject: Public Health
  topic: keywords
creator: Ellen Rose
creator: Seung Lee
creator: Patrick Young
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-30
publication date: 2025-04-30
starting page: 1
ending page: 8
doi: 10.71465/fbg278

The Intersection of Biotechnology and Genetics in Agricultural Biotechnology
type: item
description: 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.
subject: Articles
  topic: section
subject: Agricultural Biotechnology
  topic: keywords
subject: Genetic Engineering
  topic: keywords
subject: CRISPR
  topic: keywords
subject: Crop Improvement
  topic: keywords
subject: Gene Editing
  topic: keywords
subject: Sustainable Agriculture
  topic: keywords
subject: Genetic Modification
  topic: keywords
subject: Pest Management
  topic: keywords
subject: Biotechnology
  topic: keywords
subject: Genomics
  topic: keywords
subject: Environmental Impact
  topic: keywords
subject: Ethical Considerations
  topic: keywords
creator: Dr. Saira Malik
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-12-31
publication date: 2024-12-31
starting page: 244
ending page: 261
doi: 10.71465/fbg81

Biotechnology and Gene Therapy: Transforming the Treatment of Genetic Diseases
type: item
description: 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.
subject: Articles
  topic: section
subject: Gene Therapy
  topic: keywords
subject: Biotechnology
  topic: keywords
subject: Genetic Diseases
  topic: keywords
subject: Gene Editing
  topic: keywords
subject: Viral Vectors
  topic: keywords
subject: Cystic Fibrosis
  topic: keywords
subject: Muscular Dystrophy
  topic: keywords
subject: Cancer Treatment
  topic: keywords
subject: Ethical Considerations
  topic: keywords
subject: Regulatory Challenges
  topic: keywords
subject: Genetic Modification
  topic: keywords
creator: Dr. Imran Qureshi
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-12-31
publication date: 2024-12-31
starting page: 229
ending page: 243
doi: 10.71465/fbg80

The Evolution of Genetic Vaccines: From Concept to Clinical Applications
type: item
description: 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.
subject: Articles
  topic: section
subject: Genetic Vaccines
  topic: keywords
subject: mRNA Vaccines
  topic: keywords
subject: DNA Vaccines
  topic: keywords
subject: Vaccine Development
  topic: keywords
subject: Immunotherapy
  topic: keywords
subject: Clinical Applications
  topic: keywords
creator: Dr. Maria Siddiqui
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-12-31
publication date: 2024-12-31
starting page: 217
ending page: 228
doi: 10.71465/fbg79

Bioethical Considerations in Human Genetic Research and Biotechnology
type: item
description: 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.
subject: Articles
  topic: section
subject: Bioethics
  topic: keywords
subject: Human Genetic Research
  topic: keywords
subject: Biotechnology
  topic: keywords
subject: Genetic Engineering
  topic: keywords
subject: Informed Consent
  topic: keywords
subject: Privacy
  topic: keywords
subject: Genetic Discrimination
  topic: keywords
subject: Ethical Guidelines
  topic: keywords
subject: Genetic Information
  topic: keywords
subject: Gene Editing
  topic: keywords
subject: Genetic Research Ethics
  topic: keywords
subject: Genetic Privacy
  topic: keywords
subject: Ethical Frameworks
  topic: keywords
subject: Biotechnology Ethics
  topic: keywords
subject: Human Genetics
  topic: keywords
creator: Dr. Ayesha Khan
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-12-31
publication date: 2024-12-31
starting page: 201
ending page: 216
doi: 10.71465/fbg78

Genetic Diversity in Biotechnology: Harnessing Variation for Improved Outcomes
type: item
description: 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.
subject: Articles
  topic: section
subject: Genetic diversity
  topic: keywords
subject: biotechnology
  topic: keywords
subject: crop improvement
  topic: keywords
subject: livestock breeding
  topic: keywords
subject: microbial applications
  topic: keywords
subject: genetic variation
  topic: keywords
subject: sustainable practices
  topic: keywords
subject: genetic resources
  topic: keywords
subject: human health
  topic: keywords
subject: biotechnology applications
  topic: keywords
creator: Dr. Saira Ahmed
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-12-31
publication date: 2024-12-31
starting page: 184
ending page: 200
doi: 10.71465/fbg77

The Role of Genomic Medicine in Cancer Treatment and Diagnosis
type: item
description: 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.
subject: Articles
  topic: section
subject: Genomic Medicine
  topic: keywords
subject: Cancer Treatment
  topic: keywords
subject: Personalized Medicine
  topic: keywords
subject: Genome Sequencing
  topic: keywords
subject: Targeted Therapy
  topic: keywords
subject: Oncogenomic
  topic: keywords
subject: Precision Oncology
  topic: keywords
subject: Genetic Mutations
  topic: keywords
subject: Bioinformatics
  topic: keywords
subject: Cancer Diagnosis
  topic: keywords
subject: Molecular Diagnostics
  topic: keywords
subject: Tumor Genomics
  topic: keywords
subject: Next-Generation Sequencing
  topic: keywords
subject: Cancer Biomarkers
  topic: keywords
subject: Therapeutic Targets
  topic: keywords
creator: Dr. Fatima Siddiqui
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-08-31
publication date: 2024-08-31
starting page: 166
ending page: 183
doi: 10.71465/fbg76

Biotechnology in Environmental Conservation: Genetic Tools for Biodiversity Preservation
type: item
description: 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.
subject: Articles
  topic: section
subject: Biotechnology
  topic: keywords
subject: Environmental Conservation
  topic: keywords
subject: Genetic Tools
  topic: keywords
subject: Biodiversity Preservation
  topic: keywords
subject: Gene Editing
  topic: keywords
subject: Genomic Monitoring
  topic: keywords
subject: Synthetic Biology
  topic: keywords
subject: Conservation Genetics
  topic: keywords
subject: Ecosystem Protection
  topic: keywords
subject: Endangered Species
  topic: keywords
subject: Climate Change
  topic: keywords
subject: Genetic Diversity
  topic: keywords
creator: Dr. Imran Ali
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-08-31
publication date: 2024-08-31
starting page: 147
ending page: 165
doi: 10.71465/fbg75

Genomics and Bioinformatics: Integrating Data for Better Genetic Insights
type: item
description: 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.
subject: Articles
  topic: section
subject: Genomics
  topic: keywords
subject: Bioinformatics
  topic: keywords
subject: Genetic Data Integration
  topic: keywords
subject: , Sequencing Technologies
  topic: keywords
subject: Data Analysis
  topic: keywords
subject: Personalized Medicine
  topic: keywords
subject: Evolutionary Genomics
  topic: keywords
subject: Agricultural Genomics
  topic: keywords
subject: Big Data
  topic: keywords
subject: Computational Biology
  topic: keywords
creator: Dr. Farah Ahmed
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-08-31
publication date: 2024-08-31
starting page: 126
ending page: 146
doi: 10.71465/fbg74

The Impact of Synthetic Biology on Genetic Research and Biotechnology
type: item
description: 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.
subject: Articles
  topic: section
subject: Synthetic biology
  topic: keywords
subject: genetic research
  topic: keywords
subject: biotechnology
  topic: keywords
subject: gene synthesis
  topic: keywords
subject: metabolic engineering
  topic: keywords
subject: therapeutic strategies
  topic: keywords
subject: genetic engineering
  topic: keywords
creator: Dr. Muhammad Usman
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-08-31
publication date: 2024-08-31
starting page: 107
ending page: 125
doi: 10.71465/fbg73

Biotechnological Approaches to Rare Genetic Disorders: Innovations and Challenges
type: item
description: 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.
subject: Articles
  topic: section
subject: Biotechnology
  topic: keywords
subject: Rare Genetic Disorders
  topic: keywords
subject: Gene Therapy
  topic: keywords
subject: Genome Editing
  topic: keywords
subject: CRISPR/Cas9
  topic: keywords
subject: Personalized Medicine
  topic: keywords
subject: Genetic Research
  topic: keywords
subject: Viral Vectors
  topic: keywords
subject: Drug Delivery Systems
  topic: keywords
subject: Ethical Considerations
  topic: keywords
subject: Regulatory Challenges
  topic: keywords
subject: Innovative Therapies
  topic: keywords
creator: Dr. Ayesha Khan
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-08-31
publication date: 2024-08-31
starting page: 88
ending page: 106
doi: 10.71465/fbg72

Genetic Modification of Microorganisms: Applications in Industry and Medicine
type: item
description: 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.
subject: Articles
  topic: section
subject: Genetic modification
  topic: keywords
subject: microorganisms
  topic: keywords
subject: CRISPR-Cas9
  topic: keywords
subject: biotechnology
  topic: keywords
subject: industrial applications
  topic: keywords
subject: gene therapy
  topic: keywords
subject: pharmaceuticals
  topic: keywords
subject: biofuels
  topic: keywords
creator: Dr. Salman Ahmed
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-04-30
publication date: 2024-04-30
starting page: 72
ending page: 87
doi: 10.71465/fbg71

Biotechnology in Agriculture: Enhancing Crop Yields and Sustainability
type: item
description: 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.
subject: Articles
  topic: section
subject: Biotechnology
  topic: keywords
subject: Agriculture
  topic: keywords
subject: Crop Yields
  topic: keywords
subject: , Genetic Engineering
  topic: keywords
subject: Plant Tissue Culture
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Bioinformatics
  topic: keywords
subject: Pest Resistance
  topic: keywords
subject: Food Security
  topic: keywords
subject: Environmental Conservation
  topic: keywords
creator: Dr. Ayesha Khan
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-04-30
publication date: 2024-04-30
starting page: 56
ending page: 71
doi: 10.71465/fbg70

Ethical Implications of Genetic Engineering: Balancing Innovation and Responsibility
type: item
description: 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.
subject: Articles
  topic: section
subject: Genetic Engineering
  topic: keywords
subject: Ethics
  topic: keywords
subject: Innovation
  topic: keywords
subject: Biotechnology
  topic: keywords
subject: Genetic Modification
  topic: keywords
subject: Responsibility
  topic: keywords
subject: Safety
  topic: keywords
subject: Equity
  topic: keywords
subject: Policy
  topic: keywords
creator: Dr. Saba Rehman
rights: Copyright (c) 2024 Frontiers in Biotechnology and Genetics
date: 2024-04-30
publication date: 2024-04-30
starting page: 37
ending page: 55
doi: 10.71465/fbg69