by Keyword: latency
Dhawan, U, Williams, JA, Windmill, JFC, Childs, P, Gonzalez-Garcia, C, Dalby, MJ, Salmeron-Sanchez, M, (2024). Engineered Surfaces That Promote Capture of Latent Proteins to Facilitate Integrin-Mediated Mechanical Activation of Growth Factors Advanced Materials 36, 2310789 
Conventional osteogenic platforms utilize active growth factors to repair bone defects that are extensive in size, but they can adversely affect patient health. Here, an unconventional osteogenic platform is reported that functions by promoting capture of inactive osteogenic growth factor molecules to the site of cell growth for subsequent integrin-mediated activation, using a recombinant fragment of latent transforming growth factor beta-binding protein-1 (rLTBP1). It is shown that rLTBP1 binds to the growth-factor- and integrin-binding domains of fibronectin on poly(ethyl acrylate) surfaces, which immobilizes rLTBP1 and promotes the binding of latency associated peptide (LAP), within which inactive transforming growth factor beta 1 (TGF-beta 1) is bound. rLTBP1 facilitates the interaction of LAP with integrin beta 1 and the subsequent mechanically driven release of TGF-beta 1 to stimulate canonical TGF-beta 1 signaling, activating osteogenic marker expression in vitro and complete regeneration of a critical-sized bone defect in vivo. An osteogenic platform that functions by capturing inactive growth factor molecules is engineered to overcome conventional challenges associated with the use of active growth factors. The platform triggers capture of inactive transforming growth factor beta-1 for its subsequent integrin-mediated activation which activates osteogenic downstream signaling in vitro and fully repairs critical-sized bone defect in vivo. image
JTD Keywords: Animals, Bone, Bone defect, Bone regeneration, Cell proliferation, Cells, Chemical activation, Defects, Differentiation, Fibronectin, Fibronectins, Growth factor, Growth factors, Humans, Integrin beta1, Integrins, Latency associated peptides, Latent tgf-beta binding proteins, Ltbp1, Osteogenesis, Osteogenic, Protein binding, Recombinant proteins, Release, Repair, Signal transduction, Surface properties, Tgf-beta, Tgf-β1, Transforming growth factor beta1, Transforming growth factors
Ferrer-Lluis, I, Castillo-Escario, Y, Montserrat, JM, Jané, R, (2021). Enhanced monitoring of sleep position in sleep apnea patients: Smartphone triaxial accelerometry compared with video-validated position from polysomnography Sensors 21, 3689
Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG.
JTD Keywords: accelerometry, actigraphy, association, biomedical signal processing, index, latency, mhealth, monitoring, pathophysiology, quality, questionnaire, score, sleep apnea, sleep position, smartphone, time, Accelerometry, Biomedical signal processing, Mhealth, Monitoring, Sleep apnea, Sleep position, Smartphone, Supine position
Estrada, L., Santamaria, J., Isetta, V., Iranzo, A., Navajas, D., Farre, R., (2010). Validation of an EEG-based algorithm for automatic detection of sleep onset in the multiple sleep latency test Proceedings of the World Congress on Engineering 2010 
World Congress on Engineering 2010 , IAENG (International Association of Engineers) (London, UK) 1, 1-3
The Multiple Sleep Latency Test (MSLT) is a standard test to objectively evaluate patients with excessive daytime sleepiness. Sleep onset latencies are determined by visual analysis, which is costly and time-consuming. The aim of this study was to implement and test a single automatic algorithm to detect the sleep onset in the MSLT on the basis of
electroencephalographic (EEG) signals. The designed algorithm computed the relative EEG spectral powers in the occipital area and detected the sleep onset corresponding to the intersection point between the lower and alpha frequencies. The algorithm performance was evaluated by comparing the sleep latencies computed automatically by the algorithm and by a sleep specialist using MSLT recordings from a total of 19 patients (95 naps). The mean difference in sleep latency between the two methods was 0.025 min and the limits of agreement were ± 2.46 min (Bland-Altman analysis). Moreover, the intra-class correlation coefficient showed a considerable inter-rater reliability (0.90). The algorithm accurately detected the sleep onset in the MSLT. The devised algorithm can be a useful tool to support and speed up the sleep specialist’s work in routine clinical MSLT assessment.
JTD Keywords: Automatic Algorithm, Drowsiness, Electroencephalography, Multiple Sleep Latency Test, Polysomnography, Sleep onset
