{"results":[{"id":"ss_965f87c940b57242dfd2d8a3724508d10f7ae418","title":"Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation","authors":[{"name":"C. Feudtner"},{"name":"J. Feinstein"},{"name":"Wenjun Zhong"},{"name":"M. Hall"},{"name":"D. Dai"}],"abstract":"BackgroundThe pediatric complex chronic conditions (CCC) classification system, developed in 2000, requires revision to accommodate the International Classification of Disease 10th Revision (ICD-10). To update the CCC classification system, we incorporated ICD-9 diagnostic codes that had been either omitted or incorrectly specified in the original system, and then translated between ICD-9 and ICD-10 using General Equivalence Mappings (GEMs). We further reviewed all codes in the ICD-9 and ICD-10 systems to include both diagnostic and procedural codes indicative of technology dependence or organ transplantation. We applied the provisional CCC version 2 (v2) system to death certificate information and 2 databases of health utilization, reviewed the resulting CCC classifications, and corrected any misclassifications. Finally, we evaluated performance of the CCC v2 system by assessing: 1) the stability of the system between ICD-9 and ICD-10 codes using data which included both ICD-9 codes and ICD-10 codes; 2) the year-to-year stability before and after ICD-10 implementation; and 3) the proportions of patients classified as having a CCC in both the v1 and v2 systems.ResultsThe CCC v2 classification system consists of diagnostic and procedural codes that incorporate a new neonatal CCC category as well as domains of complexity arising from technology dependence or organ transplantation. CCC v2 demonstrated close comparability between ICD-9 and ICD-10 and did not detect significant discontinuity in temporal trends of death in the United States. Compared to the original system, CCC v2 resulted in a 1.0% absolute (10% relative) increase in the number of patients identified as having a CCC in national hospitalization dataset, and a 0.4% absolute (24% relative) increase in a national emergency department dataset.ConclusionsThe updated CCC v2 system is comprehensive and multidimensional, and provides a necessary update to accommodate widespread implementation of ICD-10.","source":"Semantic Scholar","year":2014,"language":"en","subjects":["Medicine"],"doi":"10.1186/1471-2431-14-199","url":"https://www.semanticscholar.org/paper/965f87c940b57242dfd2d8a3724508d10f7ae418","pdf_url":"https://bmcpediatr.biomedcentral.com/counter/pdf/10.1186/1471-2431-14-199","is_open_access":true,"citations":1526,"published_at":"","score":88},{"id":"arxiv_2603.01172","title":"Midterm Status Report of the ILC Technology Network Activities","authors":[{"name":"ILC Technology Network"}],"abstract":"The ILC Technology Network (ITN) was established in 2022 by the ILC International Development Team, a subcommittee of the International Committee for Future Accelerators, to advance engineering studies toward the realisation of the International Linear Collider (ILC). While the ITN work packages focus on engineering activities for the ILC, their topics are also relevant to a broad range of accelerator applications in particle physics and beyond. These work packages are being carried out now by laboratories in Asia and Europe in close collaboration. This report summarises the current status of the ITN activities.","source":"arXiv","year":2026,"language":"en","subjects":["physics.acc-ph","hep-ex","hep-ph"],"url":"https://arxiv.org/abs/2603.01172","pdf_url":"https://arxiv.org/pdf/2603.01172","is_open_access":true,"published_at":"2026-03-01T16:22:42Z","score":70},{"id":"ss_dbc77d5f5c6d3e3f8bce18e396d12f9585f3cc70","title":"Current state of the art and future directions for implantable sensors in medical technology: Clinical needs and engineering challenges","authors":[{"name":"David Yogev"},{"name":"Tomer Goldberg"},{"name":"Amir Arami"},{"name":"Shai Tejman-Yarden"},{"name":"Thomas E Winkler"},{"name":"Ben M. Maoz"}],"abstract":"Implantable sensors have revolutionized the way we monitor biophysical and biochemical parameters by enabling real-time closed-loop intervention or therapy. These technologies align with the new era of healthcare known as healthcare 5.0, which encompasses smart disease control and detection, virtual care, intelligent health management, smart monitoring, and decision-making. This review explores the diverse biomedical applications of implantable temperature, mechanical, electrophysiological, optical, and electrochemical sensors. We delve into the engineering principles that serve as the foundation for their development. We also address the challenges faced by researchers and designers in bridging the gap between implantable sensor research and their clinical adoption by emphasizing the importance of careful consideration of clinical requirements and engineering challenges. We highlight the need for future research to explore issues such as long-term performance, biocompatibility, and power sources, as well as the potential for implantable sensors to transform healthcare across multiple disciplines. It is evident that implantable sensors have immense potential in the field of medical technology. However, the gap between research and clinical adoption remains wide, and there are still major obstacles to overcome before they can become a widely adopted part of medical practice.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Medicine"],"doi":"10.1063/5.0152290","url":"https://www.semanticscholar.org/paper/dbc77d5f5c6d3e3f8bce18e396d12f9585f3cc70","pdf_url":"https://doi.org/10.1063/5.0152290","is_open_access":true,"citations":83,"published_at":"","score":69.49000000000001},{"id":"crossref_10.1038/s41598-025-95085-9","title":"Acute effects of air pollutants on influenza-like illness in Hangzhou, China","authors":[{"name":"Ye Lv"},{"name":"Hong Xu"},{"name":"Zhou Sun"},{"name":"Muwen Liu"},{"name":"Shanshan Xu"},{"name":"Jing Wang"},{"name":"Chaokang Li"},{"name":"Hui Ye"},{"name":"Xuhui Yang"}],"abstract":"","source":"CrossRef","year":2025,"language":"en","subjects":null,"doi":"10.1038/s41598-025-95085-9","url":"https://doi.org/10.1038/s41598-025-95085-9","pdf_url":"https://www.nature.com/articles/s41598-025-95085-9.pdf","is_open_access":true,"citations":3,"published_at":"","score":69.09},{"id":"doaj_10.24908/pocusj.v10i01.17785","title":"The Utilization of Point of Care Ultrasound (POCUS) for the Confirmation of Gastric and Post-Pyloric Feeding Tube Placement in a Pediatric Intensive Care Unit","authors":[{"name":"Alonso Marron"},{"name":"Michael Wolf"},{"name":"Marla Levine"},{"name":"Jeremy Boyd"},{"name":"Marta Hernanz-Schulman"}],"abstract":"\nThe aim of this study was to investigate the role of point of care ultrasound (POCUS) as an alternative imaging modality to confirm the location of gastric and post-pyloric feeding tubes in patients admitted to the pediatric intensive care unit (PICU). This was a prospective descriptive study performed at a tertiary care children’s hospital. Patients from birth to 17 years of age in whom the medical team placed a temporary enteral feeding tube were eligible for enrollment. The study physician, who was blinded to the radiographic findings, performed a POCUS study of the abdomen. An abdominal radiograph was obtained to confirm the placement in all patients. A total of 13 patients were enrolled, and 14 abdominal POCUS exams were completed. POCUS accurately identified the location of the enteral feeding tube in 10 of the 14 cases. POCUS had a sensitivity and specificity of 85.7% and 57.1%, respectively, in identifying gastric tubes. It had a sensitivity and specificity of 66.7% and 87.5%, respectively, in identifying post-pyloric tubes. No adverse events were reported. This study showed that POCUS had moderate sensitivity and specificity and was, overall, safe. Further studies can assess the level of training needed for improvement in accuracy, and larger studies can help support the findings of this data that POCUS is a safe and accurate alternative to radiographs for enteral feeding tube placement confirmation.\n","source":"DOAJ","year":2025,"language":"","subjects":["Internal medicine","Medical technology"],"doi":"10.24908/pocusj.v10i01.17785","url":"https://ojs.library.queensu.ca/index.php/pocus/article/view/17785","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1186/s12982-025-00422-y","title":"Understanding Nigeria’s antibiotic resistance crisis among neonates and its future implications","authors":[{"name":"Victor Oluwatomiwa Ajekiigbe"},{"name":"Ikponmwosa Jude Ogieuhi"},{"name":"Temiloluwa Adebayo Odeniyi"},{"name":"Praise Oluwatobi Ogunleke"},{"name":"Josiah Temitope Olatunde"},{"name":"Adedoyin Veronica Babalola"},{"name":"Akintunde Abisoye Omoleke"},{"name":"Tolulope Felix Omitade"},{"name":"Damilare Emmanuel Olakanmi"},{"name":"Adewunmi Akingbola"},{"name":"Chidera Stanley Anthony"}],"abstract":"Abstract A well-documented mounting public health crisis is the antibiotic crisis, which is most significantly felt in low-resource countries like Nigeria. This article sheds light on the rising level of antibiotic resistance in newborns in Nigeria, a trend that poses a severe threat to neonatal survival and public health at large. A thorough database search was carried out using terms associated with antibiotic resistance in Nigerian neonates, including PubMed, Google Scholar, and other scholarly sources. Only original research conducted between the start of the study and June 2024 was included; articles without an English translation were not. Independent reviewers handled data management and screening. There has been an increasing prevalence of sepsis among newborns primarily due to Gram-negative bacteria, which highlights the urgency and need to be addressed. Studies show a significant rise in multi-drug-resistant infections, with almost half of Escherichia coli and 86% of Staphylococcus aureus strains among newborns resistant to conventionally used antibiotics like penicillin. Some reasons for the continuous trend include but are not limited to unregulated antibiotic purchase and use, inadequate surveillance systems, and cultural determinants and socioeconomic issues. Effective strategies are needed to curb the neonatal antibiotic crisis in Nigeria. This problem can be mitigated by enhancing public education, strengthening healthcare infrastructure, advocating for better maternal health, and promoting the rational use of antibiotics. Additionally, more research into non-antibiotic medications and understanding the barriers to compliance need to be addressed.","source":"DOAJ","year":2025,"language":"","subjects":["Public aspects of medicine"],"doi":"10.1186/s12982-025-00422-y","url":"https://doi.org/10.1186/s12982-025-00422-y","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1186/s12943-024-02221-6","title":"Unveiling the immunomodulatory dance: endothelial cells’ function and their role in non-small cell lung cancer","authors":[{"name":"Sophia Daum"},{"name":"Lilith Decristoforo"},{"name":"Mira Mousa"},{"name":"Stefan Salcher"},{"name":"Christina Plattner"},{"name":"Baharak Hosseinkhani"},{"name":"Zlatko Trajanoski"},{"name":"Dominik Wolf"},{"name":"Peter Carmeliet"},{"name":"Andreas Pircher"}],"abstract":"Abstract The dynamic interactions between tumor endothelial cells (TECs) and the immune microenvironment play a critical role in the progression of non-small cell lung cancer (NSCLC). In general, endothelial cells exhibit diverse immunomodulatory properties, influencing immune cell recruitment, antigen presentation, and regulation of immune checkpoint expression. Understanding the multifaceted roles of TECs as well as assigning specific functional hallmarks to various TEC phenotypes offer new avenues for targeted development of therapeutic interventions, particularly in the context of advanced immunotherapy and anti-angiogenic treatments. This review provides insights into the complex interplay between TECs and the immune system in NSCLC including discussion of potential optimized therapeutic opportunities.","source":"DOAJ","year":2025,"language":"","subjects":["Neoplasms. Tumors. Oncology. Including cancer and carcinogens"],"doi":"10.1186/s12943-024-02221-6","url":"https://doi.org/10.1186/s12943-024-02221-6","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1051/bioconf/202516403001","title":"Effect of zero-valent iron on Rhizobium sp. cells isolated from cadmium-contaminated sites after remediation by zero-valent iron","authors":[{"name":"Nuiyen Aussanee"},{"name":"Khumin Vinta"},{"name":"Wichai Siriwan"}],"abstract":"Cadmium contamination found in paddy fields in the Maesot District of Tak Province, Thailand. This area was remediated using 50mg/L of ZVI. The study aimed to isolate and identify soil bacteria in the soil and rice roots and to investigate ZVI’s effect on the isolated bacterial cells. The results indicated no significant difference in soil bacteria content before and after remediation at the 95% confidence level. Twelve isolates of nitrogen-fixing bacteria were obtained. Those isolates could grow at high concentrations of 300 mg/L of ZVI. RH17 had a high tolerance for TSA with 300 mg/L of ZVI at only 10 CFU/ml. The effects of ZVI at 150 mg/L on RH17 cells, a small amount of ZVI was observed adhering to the cells’ surface and forming giant cells, while at 300 mg/L of ZVI, caused a reduction in growth by 81.0%. The nifH gene of RH17 was related to Rhizobium sp. strain 5-1-2. The results demonstrated the cadmium remediation process with 50mg/L of ZVI did not affect the cell count of soil bacteria in the paddy field. However, at 150 mg/L or higher, ZVI damaged the isolated Rhizobium sp. cell membrane. So, the remediation using ZVI must consider the appropriate concentration.","source":"DOAJ","year":2025,"language":"","subjects":["Microbiology","Physiology","Zoology"],"doi":"10.1051/bioconf/202516403001","url":"https://www.bio-conferences.org/articles/bioconf/pdf/2025/15/bioconf_icaaa2025_03001.pdf","pdf_url":"https://www.bio-conferences.org/articles/bioconf/pdf/2025/15/bioconf_icaaa2025_03001.pdf","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1016/j.bioactmat.2024.10.025","title":"Recent advances in surface functionalization of cardiovascular stents","authors":[{"name":"Chuanzhe Wang"},{"name":"Jie Lv"},{"name":"Mengyi Yang"},{"name":"Yan Fu"},{"name":"Wenxuan Wang"},{"name":"Xin Li"},{"name":"Zhilu Yang"},{"name":"Jing Lu"}],"abstract":"Cardiovascular diseases (CVD) are the leading global threat to human health. The clinical application of vascular stents improved the survival rates and quality of life for patients with cardiovascular diseases. However, despite the benefits stents bring to patients, there are still notable complications such as thrombosis and in-stent restenosis (ISR). Surface modification techniques represent an effective strategy to enhance the clinical efficacy of vascular stents and reduce complications. This paper reviews the development strategies of vascular stents based on surface functional coating technologies aimed at addressing the limitations in clinical application, including the inhibition of intimal hyperplasia, promotion of re-endothelialization. These strategies have improved endothelial repair and inhibited vascular remodeling, thereby promoting vascular healing post-stent implantation. However, the pathological microenvironment of target vessels and the lipid plaques are key pathological factors in the development of atherosclerosis (AS) and impaired vascular repair after percutaneous coronary intervention (PCI). Therefore, restoring normal physiological environment and removing the plaques are also treatment focuses after PCI for promoting vascular repair. Unfortunately, research in this area is limited. This paper reviews the advancements in vascular stents based on surface engineering technologies over the past decade, providing guidance for the development of stents.","source":"DOAJ","year":2025,"language":"","subjects":["Materials of engineering and construction. Mechanics of materials","Biology (General)"],"doi":"10.1016/j.bioactmat.2024.10.025","url":"http://www.sciencedirect.com/science/article/pii/S2452199X24004705","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1016/j.isci.2025.113143","title":"Influences of structural helicity of aortic dissection on endovascular repair","authors":[{"name":"Shi-Cheng Jin"},{"name":"Zi-Long Zhao"},{"name":"Xuyang Zhang"},{"name":"Peng Lv"},{"name":"Cheng Yan"},{"name":"Tiantong Xu"},{"name":"Jialing Yang"},{"name":"Lixin Wang"},{"name":"Zhihui Dong"},{"name":"Daqiao Guo"},{"name":"Xi-Qiao Feng"},{"name":"Weiguo Fu"},{"name":"Baolei Guo"}],"abstract":"Summary: Stanford type B aortic dissections often exhibit helical morphology. However, the influences of structural helicity on periprocedural and mid-to long-term adverse events after thoracic endovascular aortic repair (TEVAR) remain unclear. In this article, a total of 197 patients who underwent TEVAR between October 2019 and December 2020 were studied. Among them, 93 patients were excluded, and 104 patients were analyzed. The maximum helical angles and the maximum twists were measured using an efficient morphological method based on computed tomography angiography images. The whole dissecting aorta was divided into five zones. The visceral aortic zone exhibited the most pronounced structural helicity compared with other zones. Patients with the maximum helical angle larger or smaller than 200° were categorized into two groups, i.e., the groups of strong helicity and weak helicity. The patients in the strong helicity group exhibited a greater likelihood of experiencing adverse events after TEVAR.","source":"DOAJ","year":2025,"language":"","subjects":["Science"],"doi":"10.1016/j.isci.2025.113143","url":"http://www.sciencedirect.com/science/article/pii/S258900422501404X","is_open_access":true,"published_at":"","score":69},{"id":"arxiv_2412.01496","title":"Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets","authors":[{"name":"Nicholas Konz"},{"name":"Richard Osuala"},{"name":"Preeti Verma"},{"name":"Yuwen Chen"},{"name":"Hanxue Gu"},{"name":"Haoyu Dong"},{"name":"Yaqian Chen"},{"name":"Andrew Marshall"},{"name":"Lidia Garrucho"},{"name":"Kaisar Kushibar"},{"name":"Daniel M. Lang"},{"name":"Gene S. Kim"},{"name":"Lars J. Grimm"},{"name":"John M. Lewin"},{"name":"James S. Duncan"},{"name":"Julia A. Schnabel"},{"name":"Oliver Diaz"},{"name":"Karim Lekadir"},{"name":"Maciej A. Mazurowski"}],"abstract":"Determining whether two sets of images belong to the same or different distributions or domains is a crucial task in modern medical image analysis and deep learning; for example, to evaluate the output quality of image generative models. Currently, metrics used for this task either rely on the (potentially biased) choice of some downstream task, such as segmentation, or adopt task-independent perceptual metrics (e.g., Fréchet Inception Distance/FID) from natural imaging, which we show insufficiently capture anatomical features. To this end, we introduce a new perceptual metric tailored for medical images, FRD (Fréchet Radiomic Distance), which utilizes standardized, clinically meaningful, and interpretable image features. We show that FRD is superior to other image distribution metrics for a range of medical imaging applications, including out-of-domain (OOD) detection, the evaluation of image-to-image translation (by correlating more with downstream task performance as well as anatomical consistency and realism), and the evaluation of unconditional image generation. Moreover, FRD offers additional benefits such as stability and computational efficiency at low sample sizes, sensitivity to image corruptions and adversarial attacks, feature interpretability, and correlation with radiologist-perceived image quality. Additionally, we address key gaps in the literature by presenting an extensive framework for the multifaceted evaluation of image similarity metrics in medical imaging -- including the first large-scale comparative study of generative models for medical image translation -- and release an accessible codebase to facilitate future research. Our results are supported by thorough experiments spanning a variety of datasets, modalities, and downstream tasks, highlighting the broad potential of FRD for medical image analysis.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CV","cs.LG","eess.IV","stat.ML"],"doi":"10.1016/j.media.2026.103943","url":"https://arxiv.org/abs/2412.01496","pdf_url":"https://arxiv.org/pdf/2412.01496","is_open_access":true,"published_at":"2024-12-02T13:49:14Z","score":68},{"id":"arxiv_2407.03548","title":"HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation","authors":[{"name":"Tao Chen"},{"name":"Chenhui Wang"},{"name":"Zhihao Chen"},{"name":"Yiming Lei"},{"name":"Hongming Shan"}],"abstract":"Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discriminative; i.e., they aim to learn a mapping from the input image to segmentation masks. However, these discriminative methods neglect the underlying data distribution and intrinsic class characteristics, suffering from unstable feature space. In this work, we propose to complement discriminative segmentation methods with the knowledge of underlying data distribution from generative models. To that end, we propose a novel hybrid diffusion framework for medical image segmentation, termed HiDiff, which can synergize the strengths of existing discriminative segmentation models and new generative diffusion models. HiDiff comprises two key components: discriminative segmentor and diffusion refiner. First, we utilize any conventional trained segmentation models as discriminative segmentor, which can provide a segmentation mask prior for diffusion refiner. Second, we propose a novel binary Bernoulli diffusion model (BBDM) as the diffusion refiner, which can effectively, efficiently, and interactively refine the segmentation mask by modeling the underlying data distribution. Third, we train the segmentor and BBDM in an alternate-collaborative manner to mutually boost each other. Extensive experimental results on abdomen organ, brain tumor, polyps, and retinal vessels segmentation datasets, covering four widely-used modalities, demonstrate the superior performance of HiDiff over existing medical segmentation algorithms, including the state-of-the-art transformer- and diffusion-based ones. In addition, HiDiff excels at segmenting small objects and generalizing to new datasets. Source codes are made available at https://github.com/takimailto/HiDiff.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CV"],"doi":"10.1109/TMI.2024.3424471","url":"https://arxiv.org/abs/2407.03548","pdf_url":"https://arxiv.org/pdf/2407.03548","is_open_access":true,"published_at":"2024-07-03T23:59:09Z","score":68},{"id":"arxiv_2406.17608","title":"Test-time generative augmentation for medical image segmentation","authors":[{"name":"Xiao Ma"},{"name":"Yuhui Tao"},{"name":"Zetian Zhang"},{"name":"Yuhan Zhang"},{"name":"Xi Wang"},{"name":"Sheng Zhang"},{"name":"Zexuan Ji"},{"name":"Yizhe Zhang"},{"name":"Qiang Chen"},{"name":"Guang Yang"}],"abstract":"Medical image segmentation is critical for clinical diagnosis, treatment planning, and monitoring, yet segmentation models often struggle with uncertainties stemming from occlusions, ambiguous boundaries, and variations in imaging devices. Traditional test-time augmentation (TTA) techniques typically rely on predefined geometric and photometric transformations, limiting their adaptability and effectiveness in complex medical scenarios. In this study, we introduced Test-Time Generative Augmentation (TTGA), a novel augmentation strategy specifically tailored for medical image segmentation at inference time. Different from conventional augmentation strategies that suffer from excessive randomness or limited flexibility, TTGA leverages a domain-fine-tuned generative model to produce contextually relevant and diverse augmentations tailored to the characteristics of each test image. Built upon diffusion model inversion, a masked null-text inversion method is proposed to enable region-specific augmentations during sampling. Furthermore, a dual denoising pathway is designed to balance precise identity preservation with controlled variability. We demonstrate the efficacy of our TTGA through extensive experiments across three distinct segmentation tasks spanning nine datasets. Our results consistently demonstrate that TTGA not only improves segmentation accuracy (with DSC gains ranging from 0.1% to 2.3% over the baseline) but also offers pixel-wise error estimation (with DSC gains ranging from 1.1% to 29.0% over the baseline). The source code and demonstration are available at: https://github.com/maxiao0234/TTGA.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CV"],"doi":"10.1016/j.media.2025.103902","url":"https://arxiv.org/abs/2406.17608","pdf_url":"https://arxiv.org/pdf/2406.17608","is_open_access":true,"published_at":"2024-06-25T14:53:01Z","score":68},{"id":"arxiv_2408.08070","title":"MambaMIM: Pre-training Mamba with State Space Token Interpolation and its Application to Medical Image Segmentation","authors":[{"name":"Fenghe Tang"},{"name":"Bingkun Nian"},{"name":"Yingtai Li"},{"name":"Zihang Jiang"},{"name":"Jie Yang"},{"name":"Wei Liu"},{"name":"S. Kevin Zhou"}],"abstract":"Recently, the state space model Mamba has demonstrated efficient long-sequence modeling capabilities, particularly for addressing long-sequence visual tasks in 3D medical imaging. However, existing generative self-supervised learning methods have not yet fully unleashed Mamba's potential for handling long-range dependencies because they overlook the inherent causal properties of state space sequences in masked modeling. To address this challenge, we propose a general-purpose pre-training framework called MambaMIM, a masked image modeling method based on a novel TOKen-Interpolation strategy (TOKI) for the selective structure state space sequence, which learns causal relationships of state space within the masked sequence. Further, MambaMIM introduces a bottom-up 3D hybrid masking strategy to maintain a masking consistency across different architectures and can be used on any single or hybrid Mamba architecture to enhance its multi-scale and long-range representation capability. We pre-train MambaMIM on a large-scale dataset of 6.8K CT scans and evaluate its performance across eight public medical segmentation benchmarks. Extensive downstream experiments reveal the feasibility and advancement of using Mamba for medical image pre-training. In particular, when we apply the MambaMIM to a customized architecture that hybridizes MedNeXt and Vision Mamba, we consistently obtain the state-of-the-art segmentation performance. The code is available at: https://github.com/FengheTan9/MambaMIM.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CV"],"doi":"10.1016/j.media.2025.103606","url":"https://arxiv.org/abs/2408.08070","pdf_url":"https://arxiv.org/pdf/2408.08070","is_open_access":true,"published_at":"2024-08-15T10:35:26Z","score":68},{"id":"doaj_10.3389/fviro.2024.1459021","title":"Seroprevalence of dengue, yellow fever, and related flaviviruses among the rural human population in Nguruman and Kerio Valley, Kenya","authors":[{"name":"Mercy Hokah Kibathi"},{"name":"Mercy Hokah Kibathi"},{"name":"Edith Chepkorir"},{"name":"Sepha Nyatichi Mabeya"},{"name":"David P. Tchouassi"},{"name":"Rosemary Sang"}],"abstract":"BackgroundYellow fever virus (YFV) and dengue virus (DENV) are among the major re-emerging arboviruses that pose a significant threat to public health. Their associated burden and prevalence can be substantially underestimated due to insufficient surveillance and inadequate diagnosis. This study aimed to determine evidence of dengue, yellow and related flaviviruses circulation among the rural human populations residing in Nguruman (Kajiado County) and Kerio Valley (Baringo County), two dryland ecosystems in the Kenyan Rift Valley.MethodsSerum samples obtained from febrile patients between 5 and 85 years through a hospital-based cross-sectional survey from July 2020 – May 2023, were screened for neutralizing antibodies to YFV, DENV-2 and related flaviviruses, West Nile virus (WNV) and Zika virus (ZIKV) via Plaque reduction neutralization test (PRNT). The study sites and important demographic characteristics were obtained using a structural questionnaire and the data analyzed and seroprevalence compared. A multinomial logistic regression model was done to predict risk for each of the most prevalent viruses with covariates; age, gender, and occupation.ResultsOverall, 54.5% (50.1–59.0% 95% confidence interval (CI) of the samples tested positive for at least one of the four Flaviviruses. The percentage was significantly higher in Kerio Valley (64.34%, 184/286) than in Nguruman (40.2%, 78/194) (P\u0026lt;0.0001). YFV had the highest prevalence, followed by WNV (16.25%), ZIKV (5.2%), and DENV-2 (1%). Kerio Valley had a significantly higher YFV seroprevalence (51%) than Nguruman (6%) (P\u0026lt;0.0001), while DENV-2 was observed only in Nguruman with a low seropositivity of 2%. In contrast to Nguruman, where seropositivity rates were higher in males at 47.47% (P=0.049), in Kerio Valley, females showed considerably higher viral seropositivity at 60.82% than males (P\u0026lt;0001).ConclusionThe study suggests that there is significant circulation of Flaviviruses in both regions, posing a public health risk, that could potentially contribute to clinical disease. However, seropositivity rates vary for each specific site. Furthermore, there could be a risk of YFV, WNV, and ZIKV transmission in both sites with DENV transmission specifically noted in Nguruman. The study findings inform direct cost-effective actions (such as YF vaccines) and precise surveillance data of vector populations for improved disease risk prediction.","source":"DOAJ","year":2024,"language":"","subjects":["Microbiology"],"doi":"10.3389/fviro.2024.1459021","url":"https://www.frontiersin.org/articles/10.3389/fviro.2024.1459021/full","is_open_access":true,"published_at":"","score":68},{"id":"doaj_10.1016/j.isci.2024.110649","title":"Human RP105 monoclonal antibody enhances antigen-specific antibody production in unique culture conditions","authors":[{"name":"Tatsuya Yamazaki"},{"name":"Kenta Iwasaki"},{"name":"Susumu Tomono"},{"name":"Masaki Imai"},{"name":"Yuko Miwa"},{"name":"Masato Shizuku"},{"name":"Satoshi Ashimine"},{"name":"Kohei Ishiyama"},{"name":"Masanori Inui"},{"name":"Daisuke Okuzaki"},{"name":"Manabu Okada"},{"name":"Takaaki Kobayashi"},{"name":"Sachiko Akashi-Takamura"}],"abstract":"Summary: Detecting antibodies, particularly those targeting donor human leukocyte antigens in organ transplantation and self-antigens in autoimmune diseases, is crucial for diagnosis and therapy. Radioprotective 105 (RP105), a Toll-like receptor family protein, is expressed in immune-competent cells, such as B cells. Studies in mice have shown that the anti-mouse RP105 antibody strongly activates B cells and triggers an adjuvant effect against viral infections. However, the anti-human RP105 antibody (ɑhRP105) weakly activates human B cells. This study established new culture conditions under, which human B cells are strongly activated by the ɑhRP105. When combined with CpGDNA, specific antibody production against blood group carbohydrates, ɑGal, and SARS-CoV-2 was successfully detected in human B cell cultures. Furthermore, comprehensive analysis using liquid chromatography-electrospray ionization tandem mass spectrometry, single-cell RNA sequencing, and quantitative real-time PCR revealed that ɑhRP105 triggered a different activation stimulus compared to CpGDNA. These findings could help identify antibody-producing B cells in cases of transplant rejection and autoimmune diseases.","source":"DOAJ","year":2024,"language":"","subjects":["Science"],"doi":"10.1016/j.isci.2024.110649","url":"http://www.sciencedirect.com/science/article/pii/S2589004224018741","is_open_access":true,"published_at":"","score":68},{"id":"doaj_10.22074/ijfs.2023.1989173.1433","title":"The Decellularized Calf Testis: Introducing Suitable Scaffolds for Spermatogenesis Studies","authors":[{"name":"Mohammad Rasool Khazaei"},{"name":"Zahra Ami"},{"name":"Mozafar Khazaei"},{"name":"Leila Rezakhani"}],"abstract":"Background: Men’s infertility and lack of production of healthy and active sperm are concerns of recent years in mostcountries. Studies on the preparation of extracellular matrix (ECM) from decellularization of testis tissue and spermatogenesiscould provide proper results to solve some of the men’s infertility problems. This study aims to decellularize calftestis by different methods to reach a suitable scaffold and introduce it in spermatogenesis studies.Materials and Methods: In this experimental study, calf testis were decellularized by a freeze-de freeze, 1% sodiumdeoxycholate (SD), 0.1% sodium dodecyl sulfate (SDS), 0.1% SDS-vacuum, 1% SDS, 1% SDS-vacuum, and Triton-X100 methods. The content of DNA, collagen, and glycosaminoglycan (GAG) was analyzed using the kit and stainingwith Hematoxylin-Eosin, Masson’s trichrome, Alcian blue, and Orcein methods. The morphology of the scaffolds wasanalyzed with a scanning electron microscope (SEM).Results: Methods of 1% SDS, 1% SDS-vacuum, and 1% SD completely removed the cells. The preservation of collagenand GAG was confirmed using the staining kit and methods. The use of a vacuum showed greater porosity inthe SEM images. Toxicity and hemolysis were not observed in the scaffolds.Conclusion: Testis decellularization with 1% SDS and 1% SD, in addition to cell removal, could maintain the ECMstructure to a large extent without having cytotoxic and hemolysis effects.","source":"DOAJ","year":2024,"language":"","subjects":["Medicine (General)"],"doi":"10.22074/ijfs.2023.1989173.1433","url":"https://www.ijfs.ir/article_705094_ffa69689a15a18180face4869d5efbd7.pdf","is_open_access":true,"published_at":"","score":68},{"id":"ss_d27b50665daf08f315bb5777205fa0db664c4dd7","title":"Caring for children with new medical technology at home: parental perspectives","authors":[{"name":"Natalie Pitch"},{"name":"Anam Shahil"},{"name":"Samantha Mekhuri"},{"name":"M. Ambreen"},{"name":"Stephanie Chu"},{"name":"K. Keilty"},{"name":"Eyal Cohen"},{"name":"J. Orkin"},{"name":"Reshma Amin"}],"abstract":"Objectives This qualitative descriptive study explores the experiences of family caregivers (FCs) of children with medical complexity who are initiated on new medical technology in the hospital and transition to new daily life at home. The study aims to investigate FCs’ response and readiness for medical technology use, the value of education and transition support and the challenges associated with managing new medical technology in the home. Study design A qualitative descriptive approach was used to conduct and analyse 14 semistructured interviews with a group of FCs composed of 11 mothers and 3 fathers. Content analysis was used to analyse transcripts of the caregiver interviews. The study was conducted at a tertiary paediatric hospital in Toronto, Canada. Results Our study revealed three main themes: FC’s response and readiness for medical technology use, the value of education and transition support for initiation of new medical technology and the challenges associated with managing new medical technology in the home. FCs expressed emotional distress related to coping with the realisation that their child required medical technology. Although the theoretical and hands-on practice training instilled confidence in families, FCs reported feeling overwhelmed when they transitioned home with new medical technology. Finally, FCs reported significant psychological, emotional and financial challenges while caring for their technology-dependent child. Conclusions Our study reveals the unique challenges faced by FCs who care for technology-dependent children. These findings highlight the need to implement a comprehensive education and transition programme that provides longitudinal support for all aspects of care.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Medicine"],"doi":"10.1136/bmjpo-2023-002062","url":"https://www.semanticscholar.org/paper/d27b50665daf08f315bb5777205fa0db664c4dd7","pdf_url":"https://bmjpaedsopen.bmj.com/content/bmjpo/7/1/e002062.full.pdf","is_open_access":true,"citations":13,"published_at":"","score":67.39},{"id":"arxiv_2304.10517","title":"Segment Anything Model for Medical Image Analysis: an Experimental Study","authors":[{"name":"Maciej A. Mazurowski"},{"name":"Haoyu Dong"},{"name":"Hanxue Gu"},{"name":"Jichen Yang"},{"name":"Nicholas Konz"},{"name":"Yixin Zhang"}],"abstract":"Training segmentation models for medical images continues to be challenging due to the limited availability of data annotations. Segment Anything Model (SAM) is a foundation model that is intended to segment user-defined objects of interest in an interactive manner. While the performance on natural images is impressive, medical image domains pose their own set of challenges. Here, we perform an extensive evaluation of SAM's ability to segment medical images on a collection of 19 medical imaging datasets from various modalities and anatomies. We report the following findings: (1) SAM's performance based on single prompts highly varies depending on the dataset and the task, from IoU=0.1135 for spine MRI to IoU=0.8650 for hip X-ray. (2) Segmentation performance appears to be better for well-circumscribed objects with prompts with less ambiguity and poorer in various other scenarios such as the segmentation of brain tumors. (3) SAM performs notably better with box prompts than with point prompts. (4) SAM outperforms similar methods RITM, SimpleClick, and FocalClick in almost all single-point prompt settings. (5) When multiple-point prompts are provided iteratively, SAM's performance generally improves only slightly while other methods' performance improves to the level that surpasses SAM's point-based performance. We also provide several illustrations for SAM's performance on all tested datasets, iterative segmentation, and SAM's behavior given prompt ambiguity. We conclude that SAM shows impressive zero-shot segmentation performance for certain medical imaging datasets, but moderate to poor performance for others. SAM has the potential to make a significant impact in automated medical image segmentation in medical imaging, but appropriate care needs to be applied when using it.","source":"arXiv","year":2023,"language":"en","subjects":["cs.CV","cs.AI","cs.LG"],"doi":"10.1016/j.media.2023.102918","url":"https://arxiv.org/abs/2304.10517","pdf_url":"https://arxiv.org/pdf/2304.10517","is_open_access":true,"published_at":"2023-04-20T17:50:18Z","score":67},{"id":"arxiv_2311.02115","title":"Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging","authors":[{"name":"Emma A. M. Stanley"},{"name":"Raissa Souza"},{"name":"Anthony Winder"},{"name":"Vedant Gulve"},{"name":"Kimberly Amador"},{"name":"Matthias Wilms"},{"name":"Nils D. Forkert"}],"abstract":"Artificial intelligence (AI) models trained using medical images for clinical tasks often exhibit bias in the form of disparities in performance between subgroups. Since not all sources of biases in real-world medical imaging data are easily identifiable, it is challenging to comprehensively assess how those biases are encoded in models, and how capable bias mitigation methods are at ameliorating performance disparities. In this article, we introduce a novel analysis framework for systematically and objectively investigating the impact of biases in medical images on AI models. We developed and tested this framework for conducting controlled in silico trials to assess bias in medical imaging AI using a tool for generating synthetic magnetic resonance images with known disease effects and sources of bias. The feasibility is showcased by using three counterfactual bias scenarios to measure the impact of simulated bias effects on a convolutional neural network (CNN) classifier and the efficacy of three bias mitigation strategies. The analysis revealed that the simulated biases resulted in expected subgroup performance disparities when the CNN was trained on the synthetic datasets. Moreover, reweighing was identified as the most successful bias mitigation strategy for this setup, and we demonstrated how explainable AI methods can aid in investigating the manifestation of bias in the model using this framework. Developing fair AI models is a considerable challenge given that many and often unknown sources of biases can be present in medical imaging datasets. In this work, we present a novel methodology to objectively study the impact of biases and mitigation strategies on deep learning pipelines, which can support the development of clinical AI that is robust and responsible.","source":"arXiv","year":2023,"language":"en","subjects":["cs.CV","cs.AI","cs.CY","cs.LG"],"doi":"10.1093/jamia/ocae165","url":"https://arxiv.org/abs/2311.02115","pdf_url":"https://arxiv.org/pdf/2311.02115","is_open_access":true,"published_at":"2023-11-03T01:37:28Z","score":67}],"total":21451724,"page":1,"page_size":20,"sources":["CrossRef","arXiv","DOAJ","Semantic Scholar"],"query":"Medical technology"}