In-situ Printability Maps (IPM): A new approach for in-situ printability assessment with application to extrusion-based bioprinting

3D Bioprinting is an emerging field with many highly valuable applications. The most common and versatile technology is extrusion-based bioprinting, which requires extensive experimental campaigns to achieve appropriate quality of the bioprinted constructs when new bioinks or complex geometrical constructs need to be considered. This paper presents a new approach to easily guide operators and scientists to evaluate the probability of successful bioprinting in a defined window of the process parameters, starting from a small experimental campaign and relying on in-situ quality data. The proposed method consists of defining printability maps based on a probabilistic approach. These maps assess the printing outcome considering a specified acceptable deviation from the nominal geometry, which is predefined by the end-user depending on the application at hand. Even if shown with reference to extrusion-based bioprinting, the proposed method can be used with any other bioprinting process and any quality index, including categorical assessment classification. Eventually, the paper shows how the map can be combined with different quality criteria (e.g., productivity, cell viability) to define the appropriate setting, depending on the application at hand. Furthermore, the map provides a practical tool for rapid material printability assessment and robust process optimization. It offers an enhanced visual representation of the process domain, acceptable region boundaries, and their resilience to variation and uncertainties. Eventually, in-situ printability maps represent a further leap for the advancement of bioprinting toward the digital transformation, aiming at increasing the controllability and scalability of the bioprinting process

Glucose Prediction Algorithms from Continuous Monitoring Data: Assessment of Accuracy via Continuous Glucose Error-Grid Analysis.

Aim: The aim of this article was to use continuous glucose error-grid analysis (CG-EGA) to assess the accuracy of two time-series modeling methodologies recently developed to predict glucose levels ahead of time using continuous glucose monitoring (CGM) data. Methods: We considered subcutaneous time series of glucose concentration monitored every 3 minutes for 48 hours by the minimally invasive CGM sensor Glucoday\uae (Menarini Diagnostics, Florence, Italy) in 28 type 1 diabetic volunteers. Two prediction algorithms, based on first-order polynomial and autoregressive (AR) models, respectively, were considered with prediction horizons of 30 and 45 minutes and forgetting factors (ff) of 0.2, 0.5, and 0.8. CG-EGA was used on the predicted profiles to assess their point and dynamic accuracies using original CGM profiles as reference. Results: Continuous glucose error-grid analysis showed that the accuracy of both prediction algorithms is overall very good and that their performance is similar from a clinical point of view. However, the AR model seems preferable for hypoglycemia prevention. CG-EGA also suggests that, irrespective of the time-series model, the use of ff = 0.8 yields the highest accurate readings in all glucose ranges. Conclusions: For the first time, CG-EGA is proposed as a tool to assess clinically relevant performance of a prediction method separately at hypoglycemia, euglycemia, and hyperglycemia. In particular, we have shown that CG\u2011EGA can be helpful in comparing different prediction algorithms, as well as in optimizing their parameters

Glucose concentration can be predicted ahead in time from continuous glucose monitoring sensor time-series

A clinically important task in diabetes management is the prevention of hypo/hyperglycemic events. In this proof-of-concept paper, we assess the feasibility of approaching the problem with continuous glucose monitoring (CGM) devices. In particular, we study the possibility to predict ahead in time glucose levels by exploiting their recent history monitored every 3 min by a minimally invasive CGM system, the Glucoday, in 28 type 1 diabetic volunteers for 48 h. Simple prediction strategies, based on the description of past glucose data by either a first-order polynomial or a first-order autoregressive (AR) model, both with time-varying parameters determined by weighted least squares, are considered. Results demonstrate that, even by using these simple methods, glucose can be predicted ahead in time, e.g., with a prediction horizon of 30 min crossing of the hypoglycemic threshold can be predicted 20-25 min ahead in time, a sufficient margin to mitigate the event by sugar ingestion

Support for the role of Candica spp. in extensive caries lesions of children

Candida spp. are frequently detected in the mouths of children with extensive caries lesions compared with caries-free subjects. In this study we evaluated the presence of Candida spp. in association with mutans streptococci and lactobacilli in the saliva of children with dental decay, before and after anti-caries treatment. Samples of saliva from 14 children with caries lesions and from 13 caries-free subjects were evaluated for the presence of mutans streptococci, lactobacilli and Candida spp. by culture. Eleven of 14 carious subjects hosted Candida spp. in their saliva as against only 2 out of 13 subjects without caries lesions. Carious subjects were treated by adopting a conventional protocol for caries disease (rinses with a mouthwash containing 0.2% chlorhexidine and fluorine). After treatment, the salivary bacterial counts decreased for mutans streptococci and in some cases for lactobacilli, but large numbers of Candida spp. remained in the saliva of several children. The latter were treated with the antifungal drug nystatin (oral rinses) and evaluation of the level of yeasts in the saliva showed disappearance of the microorganism in several cases. The results indicate that antiseptic treatment alone for dental decay is not sufficient for the eradication of microorganisms potentially responsible for caries lesions, in particular when yeasts are present. We hypothesize that the oral cavity of children could act as a reservoir of fungi, and eradication could be needed to prevent both exacerbation of caries lesions, and colonization by Candida spp. of other host sites