Medicine in Novel Technology and Devices最新文献

{"title":"Decoding tissue mechanical heterogeneity through the integration of biomechanical imaging and single-cell spatial transcriptomics","authors":"Fan Zhang ,&nbsp;Wei Wang ,&nbsp;Wei Chen","doi":"10.1016/j.medntd.2025.100425","DOIUrl":"10.1016/j.medntd.2025.100425","url":null,"abstract":"<div><div>The mechanical microenvironment profoundly influences cell behavior, tissue organization, and disease progression. Recent advances in biomechanical imaging and single-cell multi-omics technologies have enabled the exploration of tissue heterogeneity from both physical and molecular perspectives. This review summarizes key biomechanical imaging methods and evaluates their capabilities and limitations. We further discuss computational strategies for predicting mechanical properties and highlight integrative approaches that link these predictions with single-cell/spatial omics data. These integrative strategies will pave the way for mechanobiology-informed precision medicine.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100425"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977739","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":"Engineering biomimetic lung-on-a-chip systems: Recapitulating air-liquid interface, dynamic breathing, and alveolar microenvironments for disease modeling","authors":"Juan Zhang ,&nbsp;Jing Zhou ,&nbsp;Yue Wang ,&nbsp;Yi Yang ,&nbsp;Tao Yue ,&nbsp;Cheng Chang","doi":"10.1016/j.medntd.2025.100415","DOIUrl":"10.1016/j.medntd.2025.100415","url":null,"abstract":"<div><div>The lung is a vital organ for gas exchange. Its microstructure is complex and changes in its physiology are crucial to human health. Lung disease is one of the leading causes of death worldwide, with new cases emerging every year. This highlights the urgent need to develop advanced preclinical models. While animal studies have long been valuable for drug development, there are inherent differences between animal and human pathophysiology. This has led to the development of three-dimensional (3D) microphysiological systems. In particular, the lung-on-a-chip (LOC) platform offers significant advantages by reproducing the alveolar microenvironment-a biphasic air-liquid environment, providing mechanically responsive, periodic stretching to simulate dynamic respiration under controlled microfluidic conditions. This review systematically explores the cellular components inherent in natural lung tissue (such as lung epithelial cells, endothelial cells, and fibroblasts) and its physiology, establishing design criteria for constructing bionic LOC systems. We critically evaluate state-of-the-art LOC architectures for simulating toxicological responses in conditions such as pneumonia, chronic obstructive pulmonary disease (COPD), pulmonary fibrosis (PF) and lung cancer. Ultimately, we provide a framework that addresses the limitations of existing LOC technologies, focusing future development efforts on critical areas that are essential for achieving predictive, clinically relevant models. This provides a roadmap for next-generation organ-on-chip platforms that combine engineering innovations with translational lung medicine, with the potential to transform drug discovery and personalized disease modeling.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100415"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749312","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":"Hb-O2 affinity parameters as prognostic factors for 28-day mortality in ARDS patients: A prospective study","authors":"Xiaoxi Zhong ,&nbsp;Shiyu Tao ,&nbsp;Weidan Li ,&nbsp;Ying Wang ,&nbsp;Jianlei An ,&nbsp;Zhiyong Huang ,&nbsp;Hong Zhou ,&nbsp;Jingyuan Liu ,&nbsp;Lian Zhao ,&nbsp;Lin Pu","doi":"10.1016/j.medntd.2025.100418","DOIUrl":"10.1016/j.medntd.2025.100418","url":null,"abstract":"<div><div>Measuring hemoglobin-oxygen (Hb-O₂) affinity might be helpful in prognosis of acute respiratory distress syndrome (ARDS) patients. We conducted a single-center prospective cohort study at the ICU department of Beijing Ditan Hospital Capital Medical University. The study enrolled 43 consecutive adult ARDS patients (≥ 18 years) admitted to ICU from November 2023 to January 2025. Data obtained from medical records and Hb-O₂ affinity parameters were compared between survivors and non-survivors. Logistic regressions were performed to screen potential prognosis factors in ARDS patients. A total of 42 patients were included in analysis. In a 28-day duration, 10 (23.8 ​%) patients died. We found significantly lower APACHE II scores (p=0.04) and SOFA scores (p=0.02) in the survival group at baseline. We further analyzed patients’ dynamics during ICU stays and found that P₅₀ significantly increased in survivors than non-survivors (p ​&lt; ​0.01), and the decrease in P₅₀ (odds ratio: 1.29, 95 ​% confidence interval 0.62–0.98, p=0.03) was an independent risk factor for poor outcomes. In 23 patients, we found significantly lower baseline theoretical oxygen release (TOR) in the survival group (p=0.02). Also, TOR significantly increased in the survival group but decreased in the non-survival group (p ​&lt; ​0.01) during the study period. We concluded that increases in P₅₀ and TOR are associated with better health outcomes in ARDS patients admitted to ICU, and Hb-O₂ affinity parameters may serve as potential prognostic indicators.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100418"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749313","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":"SZAtt-Net: A unified deep learning model with different attention mechanisms for schizophrenia classification from multimodal data","authors":"Arghyasree Saha ,&nbsp;Debgandhar Ghosh ,&nbsp;Farman Ali ,&nbsp;Pawan Kumar Singh","doi":"10.1016/j.medntd.2026.100428","DOIUrl":"10.1016/j.medntd.2026.100428","url":null,"abstract":"<div><div>Schizophrenia (SZ), a complicated mental illness, shows up as incorrect beliefs, perceptual distortions, poor reasoning, and neurocognitive problems. Its varied character—varying in severity, development, and therapy response—offers major diagnostic difficulty. While Magnetic Resonance Imaging (MRI) provides comprehensive structural and functional imaging for a better knowledge of the condition, Electroencephalography (EEG) with its great temporal resolution offers vital insights into neuronal malfunction in SZ. Deep learning (DL) techniques as well as advanced machine learning (ML) have been developed to improve SZ detection, therefore facilitating quick identification and improved patient recovery. This study presents SZAtt-Net, a DL framework designed for SZ detection and classification, integrating Convolutional Neural Networks (CNNs), Bidirectional Gated Recurrent Unit (BiGRU), along with Multilayer Perceptron (MLP) architectures. A key contribution of this work is the comprehensive ablation study of channel, self, spatial, and temporal attention mechanisms in DL, conducted to assess their impact on model performance across multimodal data. Notably, due to the absence of dedicated MRI datasets for SZ classification, this study repurposes an MRI segmentation dataset for classification, making it the first such attempt. As a unified model, SZAtt-Net is applied separately to three benchmark datasets—Kaggle EEG, LMSU EEG, and Hippocampus MRI—achieving accuracy rates of 99.37 % and 98.92 % using channel attention, and 96.33 % using spatial attention, respectively. The proposed framework is also benchmarked against various pre-trained models, and a Gradient-weighted Class Activation Mapping (Grad-CAM) analysis is performed to enhance interpretability. This work underscores the clinical relevance of SZAtt-Net and outlines future research directions for improving accessible and accurate diagnostic solutions for SZ.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100428"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939095","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":"Biomechanical influence of femoral stem design on periprosthetic femoral fractures in dorr type C femurs with normal bone quality","authors":"Junwei Li ,&nbsp;Qiang Zhang ,&nbsp;Min Zhang ,&nbsp;Jie Yao ,&nbsp;Bolun Liu ,&nbsp;Yichao Luan ,&nbsp;Long Shao ,&nbsp;Kun Tao ,&nbsp;Chaohua Fang ,&nbsp;Cheng-Kung Cheng","doi":"10.1016/j.medntd.2025.100423","DOIUrl":"10.1016/j.medntd.2025.100423","url":null,"abstract":"<div><div>Periprosthetic femoral fracture (PFF) is a major complication following total hip arthroplasty (THA), particularly in patients with Dorr type C femurs, which have normal bone quality. Implant selection plays a critical role in early postoperative stability, but the biomechanical influence of different femoral stem designs in this high-risk population remains unclear. In this study, CT data from a Dorr type C femur with normal bone quality, obtained from a patient with hip osteoarthritis, were used to reconstruct a three-dimensional femoral model. Six femoral stems representing different designs were implanted to construct corresponding THA finite element models. The models were subjected to a simulated stumbling condition, with progressively applied axial displacement until PFF occurred. The maximum fracture load was recorded and compared among the stem designs. The maximum fracture load, ranked from highest to lowest, was as follow: Corail (6079.26 N), Omnifit (5605.11 N), Synergy (5165.03 N), Taperloc (5030.77 N), Excia (4192.37 N), and Profemur (4034.64 N). The Excia and Profemur stems showing lower fracture loads than the peak stumbling load of approximately 8.7 times body weight (4785 N). These results suggest that, for THA in patients with Dorr type C femurs with normal bone quality, the use of Corail, Omnifit, Synergy, or Taperloc stems may be preferable for minimizing the risk of postoperative PFF.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100423"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939051","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(26)00007-X","DOIUrl":"10.1016/S2590-0935(26)00007-X","url":null,"abstract":"","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100432"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395737","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":"Advances in animal models and therapeutic evaluation systems for rheumatoid arthritis: From traditional paradigms to emerging technologies","authors":"Ziyan Wu,&nbsp;Wei Liu,&nbsp;Jianning Chu,&nbsp;Jingxin Yao,&nbsp;Yubo Fan,&nbsp;Ying Wang","doi":"10.1016/j.medntd.2026.100427","DOIUrl":"10.1016/j.medntd.2026.100427","url":null,"abstract":"<div><div>Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic synovitis and progressive joint destruction, with complex pathogenesis and significant clinical heterogeneity. Animal models serve as a critical platform bridging basic research and clinical translation, playing an indispensable role in elucidating the pathological mechanisms of RA, screening therapeutic targets, and evaluating drug efficacy. This article systematically reviews the research progress in RA animal models and therapeutic evaluation systems. Furthermore, it explores the application prospects of emerging technologies such as micro-nano materials and biosensors in RA research, while analyzing the current challenges in translational consistency and standardization of these models. Finally, it looks ahead to future developments, including organoid models and AI-assisted analysis, aiming to provide a systematic reference for precision mechanism research and individualized therapeutic strategy development in RA.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100427"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090155","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":"Texture-based deep learning for accurate classification of pigmented skin lesions using autoencoder based hair filtered balanced imageset","authors":"N.V. Ratnakishor Gade ,&nbsp;R Mahaveerakannan ,&nbsp;Srilali Siragam ,&nbsp;M Bhanurangarao","doi":"10.1016/j.medntd.2026.100431","DOIUrl":"10.1016/j.medntd.2026.100431","url":null,"abstract":"<div><div>Texture analysis plays a crucial role in image processing, particularly for classification tasks in medical imaging. In dermatology, accurate classification of pigmented skin lesion images is essential for early detection and diagnosis of skin cancers, notably melanoma—the most aggressive form. This study presents a texture-based deep learning framework for the classification of pigmented skin lesions. Gray Level Co-occurrence Matrix (GLCM) features, including contrast, homogeneity, and entropy, are extracted to characterize lesion texture in terms of roughness, regularity, and randomness. These features are subsequently used as inputs to various machine learning and deep learning classifiers. To address image artifacts, hair removal is performed using a two-stage filtering process combining image processing techniques and a convolutional autoencoder. Furthermore, image augmentation is applied to balance the dataset and improve model generalization. Experimental results demonstrate that the proposed approach achieves notable accuracy improvements when integrated with deep learning architectures, underscoring its potential for reliable skin lesion classification in clinical settings.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"29 ","pages":"Article 100431"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188481","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":"Biomechanical comparison of screw and minimally invasive locking plate fixation for calcaneal fracture stabilization: a finite element analysis and clinical study","authors":"Adisorn Chongmuenwai ,&nbsp;Natchayaphorn Singkhot ,&nbsp;Chanakan Ungboriboonpaisarn ,&nbsp;Nuttakitta Polpanich ,&nbsp;Supakit Rooppakhun","doi":"10.1016/j.medntd.2025.100416","DOIUrl":"10.1016/j.medntd.2025.100416","url":null,"abstract":"<div><div>The optimal strategy for managing fixation failure in joint depression calcaneal fractures, particularly in Sander's type-II and type-III cases, remains uncertain. The minimally invasive sinus tarsi (STA) approach has been increasingly adopted due to its reduced risk of soft tissue complications. Although the STA effectively reduces soft-tissue disruption, the biomechanical superiority of different fixation constructs remains uncertain. This study aimed to compare the biomechanical stability and clinical outcomes of three fixation techniques: screw fixation (SF), two-point without tuberosity, and two-point with tuberosity. FE analysis was performed to simulate Sander's type-II and type-III fractures, evaluating implant stress distribution and elastic strain at the fracture site in different fixation constructs. Moreover, FE models were reconstructed from CT images and validated through 3D-printed mechanical compression testing under an axial load of 300 ​N, yielding an average deviation of less than 10 ​% between experimental and simulated strains. Additionally, a retrospective clinical review included 72 patients whose postoperative outcomes were assessed using radiographic restoration and the Foot and Ankle Ability Measure. The two-point tuberosity fixation exhibited the lowest strain at the fracture site and the most favorable stress distribution, confirming its superior construct stability. This fixation achieved better maintenance of anatomical alignment and significantly higher FAAM scores (92.2 ​± ​6.0 vs. 78.8 ​± ​15.3, p ​&lt; ​0.001) compared with SF. These findings suggest integrating FE for biomechanics with a clinical study. The study demonstrates that two-point fixation incorporating tuberosity support provides enhanced stability and improved functional recovery, supporting its recommendation as an optimal minimally invasive strategy for Sander's type II and III calcaneal fractures. These results were consistent between FEA and clinical outcomes.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100416"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614220","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":"Mixed reality-based upper limb motor function assessment system: Feasibility and reliability study for PSCI rehabilitation","authors":"Songjun Du,&nbsp;Zhuohang He,&nbsp;Chenyu Wu,&nbsp;Tong Lyu,&nbsp;Moyang Liu,&nbsp;Yijin Li,&nbsp;Lu Wen,&nbsp;Xiaoyu Liu","doi":"10.1016/j.medntd.2025.100408","DOIUrl":"10.1016/j.medntd.2025.100408","url":null,"abstract":"<div><div>Post-stroke cognitive impairment (PSCI) is frequently accompanied by upper limb motor dysfunction, while traditional assessment methods are limited by high cognitive demands and subjectivity. Mixed reality (MR) technology can balance immersion and comprehensibility, offering a novel approach for automated motor function evaluation.</div><div>In this study, we developed an MR-based upper limb assessment system that integrates a virtual demonstration hand with wearable sensors to capture kinematics during seven standardized tasks derived from the Fugl-Meyer Assessment (FMA) and Action Research Arm Test (ARAT). Ten healthy participants completed video-, VR-, and MR-based assessments, followed by a one-week retest of MR and VR conditions. Subjective experience was evaluated using multidimensional questionnaires, while the reliability of objective kinematic features was examined using intraclass correlation coefficients (ICC), standard error of measurement (SEM), and coefficient of variation (CV%).</div><div>Compared with video and VR, MR achieved significantly higher ratings in usefulness, comprehensibility, satisfaction, and willingness to continue, while inducing lower fatigue and cybersickness. Presence improved after MR exposure, whereas disorientation-related cybersickness decreased. Test–retest analysis indicated good reliability for path length (ICC ​= ​0.85), average velocity (ICC ​= ​0.76), mean acceleration (ICC ​= ​0.77), and forearm velocity peaks (ICC ​= ​0.77).</div><div>The MR system demonstrated good feasibility, acceptance, and kinematic quantification performance. By reducing cognitive burden and enabling objective assessment, it shows potential as a tool for rehabilitation monitoring in PSCI populations.</div></div>","PeriodicalId":33783,"journal":{"name":"Medicine in Novel Technology and Devices","volume":"28 ","pages":"Article 100408"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267236","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}