Medicine in Novel Technology and Devices最新文献

{"title":"MDFSBP: A multi-perspective differential feature space framework for estimating blood pressure using photoplethysmography (PPG)","authors":"Haonan Zhang,&nbsp;Chenbin Ma,&nbsp;Guanglei Zhang","doi":"10.1016/j.medntd.2025.100407","DOIUrl":"10.1016/j.medntd.2025.100407","url":null,"abstract":"<div><div>Continuous and accurate blood pressure (BP) monitoring is critical for personalized hypertension management. However, most existing methods focus on absolute BP estimation, with limited attention to BP changes. To address this limitation, we propose a novel framework named Multi-Perspective Differential Feature Space (MDFSBP) for cuffless BP estimation using photoplethysmography (PPG) signals. MDFSBP extracts three perspective differential features: time-based and points-of-interest features, frequency-domain features, and physiological statistical features. Then, an adaptive Multi-Perspective Differential Feature Mapping Module (MDFMM) integrates reconstruction regularization, trend-aware classification, and self-weighted contrastive learning to enhance feature representation and strengthen the association between features and BP changes. Finally, an AutoML-based regression pipeline automates model optimization, improving predictive accuracy and deployment efficiency. To better test the model's capability in capturing BP changes, we introduce a novel abnormality-aware classification metric. We demonstrate BP estimation performance over state-of-the-art (SOTA) methods on both the Mindray and MIMIC datasets. On the Mindray dataset, the model achieves a regression error of 0.17 ​± ​5.17 ​mmHg for SBP and 0.05 ​± ​3.29 ​mmHg for DBP, with classification accuracy and F1-score reaching 85.25 ​% and 87.50 ​%, respectively. On the MIMIC dataset, it achieves −0.09 ​± ​5.70 ​mmHg for SBP and 0.12 ​± ​4.27 ​mmHg for DBP, with the classification accuracy and F1-score of 72.84 ​% and 70.66 ​%, respectively. These results highlight the effectiveness, robustness, and generalizability of the proposed framework for non-invasive, real-time, and continuous BP monitoring in both clinical and wearable healthcare systems.</div><div>© 2001 Elsevier Science. All rights reserved</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100407"},"PeriodicalIF":0.0,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational drug discovery of nitroimidazole compounds targeting Ddn protein of Mycobacterium tuberculosis: insights from QSAR modeling, ADMET, molecular docking, and molecular dynamics simulation studies","authors":"Santhanavel Murugan ,&nbsp;Anguraj Moulishankar ,&nbsp;Sowmiya Palanivel ,&nbsp;Kathiravan Muthu Kumaradoss ,&nbsp;Sundarrajan Thirugnanasambandam","doi":"10.1016/j.medntd.2025.100406","DOIUrl":"10.1016/j.medntd.2025.100406","url":null,"abstract":"<div><div>Still a major worldwide health issue, tuberculosis requires the development of new medicinal drugs. Computational techniques, including QSAR modeling, molecular docking, ADMET analysis, and molecular dynamics simulation, were used in this work, which examines the antitubercular potential of a nitroimidazole derivative targeting the Ddn protein of <em>Mycobacterium tuberculosis</em>. A multiple linear regression-based QSAR model (R² ​= ​0.8313, Q²_LOO ​= ​0.7426) created using QSARINS software shows strong prediction accuracy for anti-TB activity. Using molecular docking experiments (AutoDockTool 1.5.7), DE-5 compound was found to be the most promising molecule with a binding affinity of −7.81 ​kcal/mol and important hydrogen bonding interactions with active site residues PRO A:63, LYS A:79, and MET A:87. High bioavailability, good pharmacokinetics, and low toxicity risk were found by ADMET profiling (SwissADME). A 100 ns molecular dynamics simulation confirmed the stability of the DE-5-Ddn complex, as indicated by minimal Root Mean Square deviation, stable hydrogen bonds, low Root Mean Square Fluctuation, and compact structure reflected in Solvent Accessible Surface Area and radius of gyration values. Furthermore, MM/GBSA computations (−34.33 ​kcal/mol) confirmed a strong binding affinity and hence supporting DE-5's activity potential. These findings suggest that DE-5 is a suitable potential compound to advance the creation of new tuberculosis therapies targeting the Ddn protein. This work opens the path for logical drug design strategies in the TB battle.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100406"},"PeriodicalIF":0.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translational potential of natural bioactive-based formulations in atopic dermatitis: Current insights","authors":"Pratibha Kaushal ,&nbsp;Rajendra Awasthi","doi":"10.1016/j.medntd.2025.100404","DOIUrl":"10.1016/j.medntd.2025.100404","url":null,"abstract":"<div><div>The skin, as the body's largest organ, provides a crucial barrier against environmental hazards, including allergens, chemicals, toxins, and pathogens. A range of skin disorders, such as cancer, dermatitis, psoriasis, wounds, aging, acne, and infections, can compromise this vital function and significantly affect overall health. Natural products have emerged as a promising avenue for therapeutic intervention in these conditions. This review focuses specifically on the application of nanoformulations incorporating natural bioactives for the treatment of atopic dermatitis (AD), summarizing key <em>in vitro</em> and <em>in vivo</em> studies. Many of these natural products exhibit anti-inflammatory, antioxidant, and antimicrobial properties, often demonstrating the ability to reduce inflammatory markers like TNF-α, scavenge reactive oxygen species, induce apoptosis in cancer cells, and prevent infections. Furthermore, the review explores the potential and challenges associated with transdermal and topical delivery of these natural products. While preclinical studies offer encouraging results, further clinical trials are essential to validate their efficacy. The future of skin disease treatment may lie in combining natural products with conventional drugs and developing innovative delivery strategies. This review provides an overview of the latest advancements in natural bioactive-based formulations in AD treatment.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100404"},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging strategies and multifunctional applications of nanomaterials in modern nanomedicine","authors":"Indhumathi Kamaraj PhD ,&nbsp;Santhosh Kamaraj PhD ,&nbsp;Ganesan Shanmugam PhD","doi":"10.1016/j.medntd.2025.100400","DOIUrl":"10.1016/j.medntd.2025.100400","url":null,"abstract":"<div><div>The growing complexity of diseases, alongside the limitations of conventional therapies and the rise of multidrug resistance, underscores the pressing need for innovative treatment paradigms. Herein, we highlight the transformative potential of nanomaterials in modern nanomedicine, focusing on their ability to enable precise, targeted, and multifunctional therapeutic interventions. However, despite their promise, clinical translation remains constrained by several challenges, including immune clearance, systemic toxicity, scalability and a lack of long-term safety data. This review systematically presents emerging strategies that are redefining nanomaterial applications in medicine. These include surface functionalization strategies to enhance targeting specificity, hybrid nanomaterial systems for combined therapeutic and diagnostic (theranostic) functions, and stimuli-responsive strategies for controlled, site-specific drug release. We further examine biomimetic strategies that enable immune evasion by mimicking natural cellular membranes, and scaffold-based approaches that support tissue engineering and regenerative medicine. In the context of oncology, we explore strategies to overcome multidrug resistance through the co-delivery of chemotherapeutics and gene modulators. Finally, we emphasize the role of artificial intelligence (AI)-driven strategies in optimizing nanomaterial design, facilitating high-throughput screening, and predicting biological interactions. Collectively, these advancements offer a robust framework for developing next-generation nanotherapeutics that align with the goals of personalized medicine by improving precision, safety, and clinical efficacy.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100400"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling non-convex fractional order differential equation using dual supervision neural network for medical image quality enhancement","authors":"A. Regina Mary ,&nbsp;S. Mehar Banu","doi":"10.1016/j.medntd.2025.100401","DOIUrl":"10.1016/j.medntd.2025.100401","url":null,"abstract":"<div><div>Medical imaging is essential for modern cancer screening and diagnosis, but image quality is usually compromised in an attempt to lower patient risk. Traditional computer-aided diagnosis (CAD) systems that employ anomaly detection techniques have increased diagnostic accuracy by assisting radiologists in interpreting medical images. However, existing problems like inconsistent pixel values, computational inefficiencies, and limited generalizability hinder the successful application of AI-based models in real-time clinical settings. Due to distinct pixel intensity variation, medical images necessitate specific transformation; however, model development is complicated by the lack of standard parameter guidelines. Current models' high memory and processing requirements restrict their applicability in settings with limited resources, especially in rural areas. The need for a solution that ensures both diagnostic accuracy and computational efficiency is further highlighted by the fact that noise and artifacts in low-resolution images make it more difficult to diagnose diseases accurately. This study presents a method to improving the quality of medical images by using a non-convex fractional differential equation (NC-FODE). Pixel strength is efficiently calculated by NC-FODE to increase intensity and improve diagnostic relevance. To ensure precise and adaptable parameter setting for different image modalities, a dual supervised neural network (DSNN) is utilized to approximate partial derivatives and set upper bounds for model parameters. Using publicly available radiography datasets, it has been demonstrated that the proposed method greatly enhances image quality across a range of imaging modalities without requiring extensive pre-processing. Real-time processing appropriate for hectic clinical settings is made possible by experimental results showing improved pixel density, decreased noise, and superior computational efficiency. It can be customized for variety of clinical applications since it ensures consistency and reproducibility across different imaging datasets.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100401"},"PeriodicalIF":0.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring brain efficiency during exercise: A fNIRS graph theory analysis","authors":"Guangyue Zhu ,&nbsp;Guanghu Zhang ,&nbsp;Yichen Jiang ,&nbsp;Wenxi Li ,&nbsp;Dongsheng Xu","doi":"10.1016/j.medntd.2025.100389","DOIUrl":"10.1016/j.medntd.2025.100389","url":null,"abstract":"<div><div>This study seeks to elucidate the reduction in brain functional network connectivity during exercise compared to rest, utilizing graph theory techniques to analyze data from resting and movement phases across various exercise modalities. This study employed a graph theory approach to examine differences in brain network functions across various motor phases. The participants engaged in upper limb rehabilitation exercises, including passive, active, and resistance exercises, while functional near-infrared spectroscopy was used to monitor the motor-related cortex. Functional connectivity was reduced during exercise compared with rest, particularly during active and resistance exercises. Small-world network properties did not vary significantly between the two phases, although these properties were higher during movement under conditions of high sparsity. Both global and local efficiencies remained largely unchanged between phases. However, local efficiency increased during the active and resistance exercises in the movement phase. Node efficiency analysis indicated that the motor and supplementary motor areas played critical roles during exercise, with the movement phase exhibiting shorter path lengths. While the overall brain functional connectivity decreased during exercise, there was an improvement in the efficiency of specific brain nodes, suggesting a network mechanism that supports movement execution. During exercise, there was a decrease in whole-brain functional connectivity, yet an enhancement in brain efficiency was observed. This enhancement in functionality of specific nodes may signify the network mechanism responsible for movement execution.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100389"},"PeriodicalIF":0.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Near-infrared light-responsive photothermal-chemical synergistic antimicrobial GO-BPEI/La nanofiber membrane in the repair of skin wound inflammation","authors":"Liu Wang ,&nbsp;Lu-Yao Zhao ,&nbsp;Wen-Jie Tang ,&nbsp;Zhi-Yuan Wang ,&nbsp;Mei-Wen An ,&nbsp;Yang Liu ,&nbsp;Mei-Ling Wen ,&nbsp;Yan Wei","doi":"10.1016/j.medntd.2025.100397","DOIUrl":"10.1016/j.medntd.2025.100397","url":null,"abstract":"<div><div>Electrospun fibers are widely used in biomedical applications for tissue and organ repair due to their unique structure, which resembles the extracellular matrix (ECM). A key challenge in designing ideal wound dressings lies in simultaneously enhancing antibacterial efficacy and biocompatibility. In this study, to address chronic inflammation associated with microbial resistance, branched polyethyleneimine (BPEI)-modified graphene oxide (GO) (GO-BPEI) and LaCl₃ were incorporated into a solution composed of polyvinyl alcohol (PVA) and chitosan (CS). Through electrospinning, a PVA/CS/GO-BPEI/La nanofibrous membrane with photothermal/chemical synergistic antibacterial properties was fabricated. The resulting membranes exhibited favorable mechanical properties, breathability, and moisture absorption. The photothermal antibacterial effect of GO-BPEI, combined with the chemical antibacterial activity of LaCl₃, endowed the electrospun membranes with remarkable inhibition rates against <em>Staphylococcus aureus</em> (97 ​%) and <em>Escherichia coli</em> (99 ​%). Moreover, the membranes showed negligible cytotoxicity toward human skin fibroblasts (HSFs) and only a minor impact on cell migration. Therefore, this electrospun membrane demonstrates great potential as a skin wound dressing for infection suppression and tissue regeneration.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100397"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cover","authors":"","doi":"10.1016/S2590-0935(25)00053-0","DOIUrl":"10.1016/S2590-0935(25)00053-0","url":null,"abstract":"","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"27 ","pages":"Article 100402"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145018964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photothermal nanomaterials-based scaffolds for tissue regeneration and cancer therapy","authors":"Kuldeep Rajpoot","doi":"10.1016/j.medntd.2025.100395","DOIUrl":"10.1016/j.medntd.2025.100395","url":null,"abstract":"<div><div>Recently, photothermal therapy (PTT) has been considered a promising method for cancer treatment with fewer serious side effects compared to conventional radiation, chemotherapy and surgical resection. PTT is based on the photoconversion ability of photothermal agents (PTAs) as well as utilizes various nanomaterials (NMs) owing to their excellent photothermal properties. PTAs can penetrate tumor tissue, reduce local and systemic damage, and can be easily controlled. PTA-based composite scaffolds stimulate tissue reconstruction as well as regeneration following ablation of cancer cells, combining the advantages of photothermal NMs for maximum therapeutic efficacy with minimal side effects. Recently, hybrid PTAs as well as 3-dimensional scaffolds are being developed to maximize therapeutic efficacy along with minimal adverse effects, which make these composite scaffolds promising for biomedical applications. This review focuses on a detailed discussion on topics such as PTAs (i.e., organic polymer-based PTAs and inorganic PTAs) and PTT-mediated scaffolds for tissue regeneration such as PTA-based scaffolds, carbon NMs-based scaffolds, and gold NMs scaffolds, copper NMs-based scaffolds, iron NMs-based scaffolds, black phosphorus (BP)-based scaffolds, MXenes-based scaffolds and PTT-mediated scaffolds in cancer therapy.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100395"},"PeriodicalIF":0.0,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comprehensive Review of Deep Learning in OCT Image Segmentation and Classification","authors":"Abdo Sulaiman Abdi ,&nbsp;Adnan Mohsin Abdulazeez","doi":"10.1016/j.medntd.2025.100396","DOIUrl":"10.1016/j.medntd.2025.100396","url":null,"abstract":"<div><div>Optical Coherence Tomography (OCT) has transformed ophthalmology by enabling high-resolution imaging essential for diagnosing a wide range of ocular diseases. In recent years, Deep Learning (DL) techniques have really integrated well with OCT, bringing a significant boost in the accuracy and efficiency of automatic disease detection. This review is meant as a thorough and full-scale exploration of DL-based OCT segmentation and classification. It discusses the progress and points out key issues which need to be addressed in future research. The paper first looks at OCT datasets, their diversity, representational diseases and capacity to form reliable training sets for DL models. Then it delves into analysis with segmentation methods, compares their performance and identifies problems with existing approaches. The review surveys current classification techniques, contrasting deep learning models of various architectures which are capable of recognizing and distinguishing retinal diseases. It also focuses on the clinical significance of these models–details precisely what ocular conditions they analyze, and how well they can diagnose disease. In addition to synthesizing existing achievements, the review makes clear the major highpoints of current research as well as future directions. It identifies problems such as inadequate dataset diversity, model generality irregulatity, interpretability and computation efficiency. It makes concrete proposals for improvement, including real-world image collection and algorithm optimizations to fill in gaps in databases or increase model episode performance remarkably. This kind-of study should eventually help to provide a clear view of the present state as well as future prospects for deep learning in ophthalmic diagnosis by OCT.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100396"},"PeriodicalIF":0.0,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}