Biological evaluation of the modified nano-amorphous phosphate calcium doped with citrate/poly-amino acid composite as a potential candidate for bone repair and reconstruction

Large numbers of research works related to fabricating organic–inorganic composite materials have been carried out to mimic the natural structure of bone. In this study, a new modified n-ACP doped with citrate (n-ACP-cit)/poly (amino acids) (PAA) composite (n-ACP-cit/PAA) was synthesized by employing high bioactive n-ACP-cit and the biodegradable and biocompatible PAA copolymer. Its basic structure was characterized by X-ray diffraction spectroscopy, Fourier transformed infrared spectroscopy, and X-ray photoelectron spectroscopy. Moreover, the degradability, bioactivity, biocompatibility, and osteoconductivity of n-ACP-cit/PAA composite were evaluated in vitro and in vivo, using simulated body fluid (SBF) solution soaking test, mouse bone marrow mesenchymal stem cells proliferation and differentiation, morphological observation test, expression of genes associated with osteogenesis, and bone defect model repair test, respectively. The modified n-ACP-cit/PAA composite exhibited a much higher weight loss rate (36.01 wt.%) than that of PAA (23.99 wt.%) after immersing in SBF solution for 16 weeks and the pH values of local environment restored to neutral condition. Moreover, cells co-culturing with composites exhibited higher alkaline phosphatase activity, more calcium nodule-formation, and higher expression levels of osteogenic differentiation-related genes (Bmp-2, Colla I, OCN, OPN, and Runx-2) than that of PAA. Furthermore, the bone defect model repair test revealed that the composite could be intimately incorporated with the surrounding bone without causing any deleterious reaction and capable of guiding new bone formation. Together, these results indicated that the new modified bone repair n-ACP-cit/PAA composite material with specific characteristics may be designed for meeting diverse requirements from biomedical applications.

Automated Conversation Review to Surface Virtual Assistant Misunderstandings: Reducing Cost and Increasing Privacy

With the rise of Intelligent Virtual Assistants (IVAs), there is a necessary rise in human effort to identify conversations containing misunderstood user inputs. These conversations uncover error in natural language understanding and help prioritize and expedite improvements to the IVA. As human reviewer time is valuable and manual analysis is time consuming, prioritizing the conversations where misunderstanding has likely occurred reduces costs and speeds improvement. In addition, less conversations reviewed by humans mean less user data is exposed, increasing privacy. We present a scalable system for automated conversation review that can identify potential miscommunications. Our system provides IVA designers with suggested actions to fix errors in IVA understanding, prioritizes areas of language model repair, and automates the review of conversations where desired.Verint - Next IT builds IVAs on behalf of other companies and organizations, and therefore analyzes large volumes of conversational data. Our review system has been in production for over three years and saves our company roughly $1.5 million in annotation costs yearly, as well as shortened the refinement cycle of production IVAs. In this paper, the system design is discussed and performance in identifying errors in IVA understanding is compared to that of human reviewers.