3D Printing of Piezoelectric Barium Titanate-Hydroxyapatite Scaffolds with Interconnected Porosity for Bone Tissue Engineering

The prevalence of large bone defects is still a major problem in surgical clinics. It is, thus, not a surprise that bone-related research, especially in the field of bone tissue engineering, is a major issue in medical research. Researchers worldwide are searching for the missing link in engineering bone graft materials that mimic bones, and foster osteogenesis and bone remodeling. One approach is the combination of additive manufacturing technology with smart and additionally electrically active biomaterials. In this study, we performed a three-dimensional (3D) printing process to fabricate piezoelectric, porous barium titanate (BaTiO3) and hydroxyapatite (HA) composite scaffolds. The printed scaffolds indicate good cytocompatibility and cell attachment as well as bone mimicking piezoelectric properties with a piezoelectric constant of 3 pC/N. This work represents a promising first approach to creating an implant material with improved bone regenerating potential, in combination with an interconnected porous network and a microporosity, known to enhance bone growth and vascularization

Nitrogen regulation of protein–protein interactions and transcript levels of GlnK PII regulator and AmtB ammonium transporter homologs in Archaea

Gene homologs of GlnK PII regulators and AmtB-type ammonium transporters are often paired on prokaryotic genomes, suggesting these proteins share an ancient functional relationship. Here, we demonstrate for the first time in Archaea that GlnK associates with AmtB in membrane fractions after ammonium shock, thus, providing a further insight into GlnK-AmtB as an ancient nitrogen sensor pair. For this work, Haloferax mediterranei was advanced for study through the generation of a pyrE2-based counterselection system that was used for targeted gene deletion and expression of Flag-tagged proteins from their native promoters. AmtB1-Flag was detected in membrane fractions of cells grown on nitrate and was found to coimmunoprecipitate with GlnK after ammonium shock. Thus, in analogy to bacteria, the archaeal GlnK PII may block the AmtB1 ammonium transporter under nitrogen-rich conditions. In addition to this regulated protein–protein interaction, the archaeal amtB-glnK gene pairs were found to be highly regulated by nitrogen availability with transcript levels high under conditions of nitrogen limitation and low during nitrogen excess. While transcript levels of glnK-amtB are similarly regulated by nitrogen availability in bacteria, transcriptional regulators of the bacterial glnK promoter including activation by the two-component signal transduction proteins NtrC (GlnG, NRI) and NtrB (GlnL, NRII) and sigma factor σN (σ54) are not conserved in archaea suggesting a novel mechanism of transcriptional control

Electrically Conductive and 3D-Printable Oxidized Alginate-Gelatin Polypyrrole:PSS Hydrogels for Tissue Engineering

Electroactive hydrogels can be used to influence cell response and maturation by electrical stimulation. However, hydrogel formulations which are 3D printable, electroactive, cytocompatible, and allow cell adhesion, remain a challenge in the design of such stimuli-responsive biomaterials for tissue engineering. Here, a combination of pyrrole with a high gelatin-content oxidized alginate-gelatin (ADA-GEL) hydrogel is reported, offering 3D-printability of hydrogel precursors to prepare cytocompatible and electrically conductive hydrogel scaffolds. By oxidation of pyrrole, electroactive polypyrrole:polystyrenesulfonate (PPy:PSS) is synthesized inside the ADA-GEL matrix. The hydrogels are assessed regarding their electrical/mechanical properties, 3D-printability, and cytocompatibility. It is possible to prepare open-porous scaffolds via bioplotting which are electrically conductive and have a higher cell seeding efficiency in scaffold depth in comparison to flat 2D hydrogels, which is confirmed via multiphoton fluorescence microscopy. The formation of an interpenetrating polypyrrole matrix in the hydrogel matrix increases the conductivity and stiffness of the hydrogels, maintaining the capacity of the gels to promote cell adhesion and proliferation. The results demonstrate that a 3D-printable ADA-GEL can be rendered conductive (ADA-GEL-PPy:PSS), and that such hydrogel formulations have promise for cell therapies, in vitro cell culture, and electrical-stimulation assisted tissue engineering

On the reproducibility of extrusion-based bioprinting: round robin study on standardization in the field

The outcome of three-dimensional (3D) bioprinting heavily depends, amongst others, on the interaction between the developed bioink, the printing process, and the printing equipment. However, if this interplay is ensured, bioprinting promises unmatched possibilities in the health care area. To pave the way for comparing newly developed biomaterials, clinical studies, and medical applications (i.e. printed organs, patient-specific tissues), there is a great need for standardization of manufacturing methods in order to enable technology transfers. Despite the importance of such standardization, there is currently a tremendous lack of empirical data that examines the reproducibility and robustness of production in more than one location at a time. In this work, we present data derived from a round robin test for extrusion-based 3D printing performance comprising 12 different academic laboratories throughout Germany and analyze the respective prints using automated image analysis (IA) in three independent academic groups. The fabrication of objects from polymer solutions was standardized as much as currently possible to allow studying the comparability of results from different laboratories. This study has led to the conclusion that current standardization conditions still leave room for the intervention of operators due to missing automation of the equipment. This affects significantly the reproducibility and comparability of bioprinting experiments in multiple laboratories. Nevertheless, automated IA proved to be a suitable methodology for quality assurance as three independently developed workflows achieved similar results. Moreover, the extracted data describing geometric features showed how the function of printers affects the quality of the printed object. A significant step toward standardization of the process was made as an infrastructure for distribution of material and methods, as well as for data transfer and storage was successfully established

On the reproducibility of extrusion-based bioprinting: round robin study on standardization in the field

The outcome of three-dimensional (3D) bioprinting heavily depends, amongst others, on the interaction between the developed bioink, the printing process, and the printing equipment. However, if this interplay is ensured, bioprinting promises unmatched possibilities in the health care area. To pave the way for comparing newly developed biomaterials, clinical studies, and medical applications (i.e. printed organs, patient-specific tissues), there is a great need for standardization of manufacturing methods in order to enable technology transfers. Despite the importance of such standardization, there is currently a tremendous lack of empirical data that examines the reproducibility and robustness of production in more than one location at a time. In this work, we present data derived from a round robin test for extrusion-based 3D printing performance comprising 12 different academic laboratories throughout Germany and analyze the respective prints using automated image analysis (IA) in three independent academic groups. The fabrication of objects from polymer solutions was standardized as much as currently possible to allow studying the comparability of results from different laboratories. This study has led to the conclusion that current standardization conditions still leave room for the intervention of operators due to missing automation of the equipment. This affects significantly the reproducibility and comparability of bioprinting experiments in multiple laboratories. Nevertheless, automated IA proved to be a suitable methodology for quality assurance as three independently developed workflows achieved similar results. Moreover, the extracted data describing geometric features showed how the function of printers affects the quality of the printed object. A significant step toward standardization of the process was made as an infrastructure for distribution of material and methods, as well as for data transfer and storage was successfully established

Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro

The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results

remote: Empirical Orthogonal Teleconnections in R

In climate science, teleconnection analysis has a long standing history as a means for describing regions that exhibit above average capability of explaining variance over time within a certain spatial domain (e.g., global). The most prominent example of a global coupled ocean-atmosphere teleconnection is the El Nin ?o Southern Oscillation. There are numerous signal decomposition methods for identifying such regions, the most widely used of which are (rotated) empirical orthogonal functions. First introduced by van den Dool, Saha, and Johansson (2000), empirical orthogonal teleconnections (EOT) denote a regression based approach that allows for straight-forward interpretation of the extracted modes. In this paper we present the R implementation of the original algorithm in the remote package. To highlight its usefulness, we provide three examples of potential use- case scenarios for the method including the replication of one of the original examples from van den Dool et al. (2000). Furthermore, we highlight the algorithms use for cross- correlations between two different geographic fields (identifying sea surface temperature drivers for precipitation), as well as statistical downscaling from coarse to fine grids (using Normalized Difference Vegetation Index fields)

remote

In climate science, teleconnection analysis has a long standing history as a means for describing regions that exhibit above average capability of explaining variance over time within a certain spatial domain (e.g., global). The most prominent example of a global coupled ocean-atmosphere teleconnection is the El Nin ?o Southern Oscillation. There are numerous signal decomposition methods for identifying such regions, the most widely used of which are (rotated) empirical orthogonal functions. First introduced by van den Dool, Saha, and Johansson (2000), empirical orthogonal teleconnections (EOT) denote a regression based approach that allows for straight-forward interpretation of the extracted modes. In this paper we present the R implementation of the original algorithm in the remote package. To highlight its usefulness, we provide three examples of potential use- case scenarios for the method including the replication of one of the original examples from van den Dool et al. (2000). Furthermore, we highlight the algorithms use for cross- correlations between two different geographic fields (identifying sea surface temperature drivers for precipitation), as well as statistical downscaling from coarse to fine grids (using Normalized Difference Vegetation Index fields)