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Research Article
Challenges in Electroacupuncture Research: An Indispensable and Valuable Perspective for Understanding Electroacupuncture Mechanisms
Chen Yingqi
,
Yang Huayuan*
Issue:
Volume 13, Issue 3, September 2025
Pages:
52-56
Received:
2 May 2025
Accepted:
17 July 2025
Published:
23 July 2025
Abstract: Electroacupuncture (EA) is a green therapy, including needle insertion and electrical stimulation, which has a long history, outstanding curative effect, and wide application. The electric current is brought into the acupoint body tissues through acupuncture needles, producing various bio-electrochemical or bio-electrophysical effects. The basis of these effects is the presence of bioelectricity in the human body. Examining these effects may offer many novel perspectives, ideas, and methods for studying EA, as opposed to molecular pathways. This seemingly tangible-yet-intangible phenomenon of bioelectricity may become a breakthrough in the study of acupuncture mechanism. However, research exploring EA from this perspective remains scarce, hindered by several challenges. The field demands high technical precision, interdisciplinary expertise (spanning biophysics, neurophysiology, and bioengineering), and prolonged experimental phases, which often result in preliminary findings failing to sustain long-term validation. Additionally, the rapid advancement of modern science and technology complicates consistent methodological frameworks, rendering some research directions obsolete prematurely. Despite these obstacles, a deeper investigation into bioelectrical mechanisms is indispensable for advancing EA research. Addressing these challenges will not only enrich our understanding of EA but also pave the way for innovative therapeutic strategies in integrative medicine.Therefore, we must first have a preliminary understanding of the current state of research on EA from the perspective of bio-electronics.
Abstract: Electroacupuncture (EA) is a green therapy, including needle insertion and electrical stimulation, which has a long history, outstanding curative effect, and wide application. The electric current is brought into the acupoint body tissues through acupuncture needles, producing various bio-electrochemical or bio-electrophysical effects. The basis of...
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Review Article
The Advancements of Nanobiotechnology in Novel Drug Delivery System: Current Trends and Future Directions
Alebachew Molla*
Issue:
Volume 13, Issue 3, September 2025
Pages:
57-65
Received:
25 June 2025
Accepted:
9 July 2025
Published:
30 July 2025
DOI:
10.11648/j.ijbse.20251303.12
Downloads:
Views:
Abstract: Nanobiotechnology has revolutionized drug delivery systems by enabling precise, controlled, and targeted therapeutic interventions that significantly enhance treatment efficacy while minimizing systemic toxicity. This review comprehensively examines current trends in nanocarrier design, including liposomes, polymeric nanoparticles, dendrimers, quantum dots, and carbon nanotubes and their applications in overcoming biological barriers and improving drug bioavailability. Emphasis is placed on smart, stimuli-responsive delivery platforms and multifunctional nanomedicines that combine therapy with real-time imaging for theranostics. The article also addresses critical challenges such as nanoparticle toxicity, manufacturing scalability, and regulatory hurdles that impede clinical translation. Looking forward, emerging technologies like nanorobotics, artificial intelligence integration, and sustainable manufacturing promise to drive the next generation of personalized, precision nanomedicine. Interdisciplinary collaboration will be essential to unlock the full clinical potential of nanobiotechnology, ultimately transforming global healthcare outcomes.
Abstract: Nanobiotechnology has revolutionized drug delivery systems by enabling precise, controlled, and targeted therapeutic interventions that significantly enhance treatment efficacy while minimizing systemic toxicity. This review comprehensively examines current trends in nanocarrier design, including liposomes, polymeric nanoparticles, dendrimers, quan...
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Research Article
Advances in Artificial Intelligence-Assisted Diagnosis (AI) in Ultrasound
Issue:
Volume 13, Issue 3, September 2025
Pages:
66-71
Received:
16 July 2025
Accepted:
6 August 2025
Published:
12 August 2025
DOI:
10.11648/j.ijbse.20251303.13
Downloads:
Views:
Abstract: Artificial intelligence-assisted diagnosis (AI) has emerged as a transformative tool in medical imaging, leveraging advanced computational techniques to enhance lesion detection, characterization, and differentiation between benign and malignant conditions. While AI has gained significant traction in CT and MRI, particularly for breast and pulmonary nodule diagnosis, its application in ultrasound remains relatively nascent. Ultrasound, despite its widespread clinical utility, is highly operator-dependent, with diagnostic accuracy influenced by subjective factors. AI-assisted systems aim to mitigate these limitations by providing objective, reproducible analyses. This review explores the fundamental principles of AI-assisted diagnostic systems and their evolving role in ultrasound imaging, with a focus on key clinical applications, challenges, and future directions. The review begins by outlining the historical development and workflow of AI-assisted diagnosis, emphasizing its three core steps: image preprocessing, feature extraction, and data processing. It then delves into specific applications across diverse ultrasound domains: Thyroid Nodules: AI systems demonstrate promise in automating malignancy risk stratification, though challenges persist in real-time performance and regional nodule identification. Breast Nodules: Integration with Breast Imaging Reporting and Data System (BI-RADS）criteria enables improved classification accuracy, particularly for less experienced sonographers. Liver Fibrosis: AI-driven texture analysis of liver parenchyma and capsule geometry offers non-invasive staging tools, albeit with technical complexities due to anatomical variability. Carotid Atherosclerosis: AI aids in plaque detection and stenosis quantification, reducing operator dependence in vascular ultrasound. Myocardial Infarction: Segmentation and acoustic feature analysis enhance echocardiographic assessment of infarcted myocardium, though standardized algorithms remain under development. Additional applications in musculoskeletal imaging, obstetrics, and endoscopic ultrasound are also highlighted. While AI-assisted ultrasound diagnosis holds immense potential to improve diagnostic accuracy, workflow efficiency, and early disease detection, its clinical adoption lags behind other imaging modalities due to challenges in image standardization and algorithm robustness. Future advancements hinge on large-scale validation studies, innovations in deep learning architectures, and interdisciplinary collaboration. With continued refinement, AI is poised to revolutionize ultrasound practice, bridging gaps in precision medicine and expanding access to high-quality diagnostic care.
Abstract: Artificial intelligence-assisted diagnosis (AI) has emerged as a transformative tool in medical imaging, leveraging advanced computational techniques to enhance lesion detection, characterization, and differentiation between benign and malignant conditions. While AI has gained significant traction in CT and MRI, particularly for breast and pulmonar...
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