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Aims: The use of advanced hybrid closed loop systems is spreading due to the beneficial effects on glycometabolic control obtained in patients with type 1 diabetes. However, hypoglycemic episodes can be sometimes a matter of concern. We aim to compare the hypoglycemic risk of an advanced hybrid closed loop system and a predictive low glucose suspend sensor augmented pump.
Methods: In this retrospective three months observational study, we included 30 patients using Medtronic Minimed™ 780G advanced hybrid closed loop system and 30 patients using a Medtronic Minimed™ predictive low glucose suspend sensor augmented pump.
Results: The advanced hybrid closed loop system reduced the time spent above 180 mg/dL threshold and increased the time in range as compared to the predictive low glucose suspend. No severe hypoglycemia occurred in both groups and no differences were observed in the percentage of time spent below 70 mg/dl and 54 mg/dl glucose threshold. Nevertheless, more hypoglycemic episodes were recorded during daytime, but not in nighttime, with the use of the advanced hybrid closed loop system.
Conclusions: Our results confirmed the general improvement of glycemic outcomes obtained with the advanced hybrid closed loop system; however more hypoglycemic episodes during daytime were evident.
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http://dx.doi.org/10.1016/j.diabres.2023.111011 | DOI Listing |
Br J Cancer
September 2025
Department of Genetics, Institut Curie, PSL Research University, Paris, France.
Background: Identifying molecular alterations specific to advanced lung adenocarcinomas could provide insights into tumour progression and dissemination mechanisms.
Method: We analysed tumour samples, either from locoregional lesions or distant metastases, from patients with advanced lung adenocarcinoma from the SAFIR02-Lung trial by targeted sequencing of 45 cancer genes and comparative genomic hybridisation array and compared them to early tumours samples from The Cancer Genome Atlas.
Results: Differences in copy-number alterations frequencies suggest the involvement in tumour progression of LAMB3, TNN/KIAA0040/TNR, KRAS, DAB2, MYC, EPHA3 and VIPR2, and in metastatic dissemination of AREG, ZNF503, PAX8, MMP13, JAM3, and MTURN.
Heart
September 2025
Department of Biomedical Engineering, CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
Cardiovascular disease remains a leading cause of morbidity and mortality worldwide, with conventional management often applying standardised approaches that struggle to address individual variability in increasingly complex patient populations. Computational models, both knowledge-driven and data-driven, have the potential to reshape cardiovascular medicine by offering innovative tools that integrate patient-specific information with physiological understanding or statistical inference to generate insights beyond conventional diagnostics. This review traces how computational modelling has evolved from theoretical research tools into clinical decision support systems that enable personalised cardiovascular care.
View Article and Find Full Text PDFComput Methods Programs Biomed
September 2025
eXiT Research Group, Universitat de Girona (UdG), EPS - Edifici P-IV, Carrer Universitat de Girona, 6, Girona, 17003, Catalunya, Spain.
Background And Objective: Hybrid forecasting methods aim to overcome the limitations of classical statistical approaches and deep learning models. While statistical methods provide interpretability, they often lack predictive power. Conversely, deep learning models achieve high accuracy but act as "black boxes.
View Article and Find Full Text PDFPLoS One
September 2025
School of Computer Science, CHART Laboratory, University of Nottingham, Nottingham, United Kingdom.
Background And Objective: Male fertility assessment through sperm morphology analysis remains a critical component of reproductive health evaluation, as abnormal sperm morphology is strongly correlated with reduced fertility rates and poor assisted reproductive technology outcomes. Traditional manual analysis performed by embryologists is time-intensive, subjective, and prone to significant inter-observer variability, with studies reporting up to 40% disagreement between expert evaluators. This research presents a novel deep learning framework combining Convolutional Block Attention Module (CBAM) with ResNet50 architecture and advanced deep feature engineering (DFE) techniques for automated, objective sperm morphology classification.
View Article and Find Full Text PDFSci Adv
September 2025
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore.
Embodied intelligence in soft robotics offers unprecedented capabilities for operating in uncertain, confined, and fragile environments that challenge conventional technologies. However, achieving true embodied intelligence-which requires continuous environmental sensing, real-time control, and autonomous decision-making-faces challenges in energy management and system integration. We developed deformation-resilient flexible batteries with enhanced performance under magnetic fields inherently present in magnetically actuated soft robots, with capacity retention after 200 cycles improved from 31.
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