Development of a Simple Mechanical Screening Method for Predicting the Feedability of a Pharmaceutical FDM 3D Printing Filament

Purpose: The filament-based feeding mechanism employed by the majority of fused deposition modelling (FDM) 3D printers dictates that the materials must have very specific mechanical characteristics. Without a suitable mechanical profile, the filament can cause blockages in the printer. The purpose of this study was to develop a method to screen the mechanical properties of pharmaceutically-relevant, hot-melt extruded filaments to predetermine their suitability for FDM. Methods: A texture analyzer was used to simulate the forces a filament is subjected to inside the printer. The texture analyzer produced a force-distance curve referred to as the flexibility profile. Principal Component Analysis and Correlation Analysis statistical methods were then used to compare the flexibility profiles of commercial filaments to in-house made filaments. Results: Principal component analysis showed clearly separated clustering of filaments that suffer from mechanical defects versus filaments which are suitable for printing. Correlation scores likewise showed significantly greater values with feedable filaments than their mechanically deficient counterparts. Conclusion: The screening method developed in this study showed, with statistical significance and reproducibility, the ability to predetermine the feedability of extruded filaments into an FDM printer

Broad utility of an affinity-enrichment strategy for unanchored polyubiquitin chains

Protein ubiquitination is a common post-translational modification where selected targets are covalently modified by the ubiquitin protein, often in the form of isopeptide-linked polyubiquitin chains. More recently, unanchored (i.e. non-substrate-linked) polyubiquitin chains have also been described and implicated in a range of biological processes. The development of Tandem-repeated Ubiquitin-Binding Entities (TUBEs), engineered repeats of ubiquitin-binding domains that interact non-covalently with polyubiquitin, has allowed strategies for the affinity-enrichment of ubiquitinmodified proteins to be established, in some cases with linkage specificity. Here, we demonstrate the utility of a Free Ubiquitin-Binding Entity (FUBE), based on an ubiquitin-binding domain with high specificity for the free C-terminus of ubiquitin (the Znf-UBP domain of human USP5). In contrast to TUBEs which do not distinguish conjugated or free polyubiquitin, the FUBE exclusively recognises ubiquitin in its unconjugated form, including endogenous unanchored polyubiquitin chains. Affinity-enrichments using the FUBE demonstrate that unanchored polyubiquitin chains are present in different mammalian cell lines and accumulate when the 26S proteasome is pharmacologically inhibited, being retained on the proteasome. The high conservation of the ubiquitin sequence permits the FUBE to also be applied to the purification of endogenous unanchored polyubiquitin chains from species as diverse as Arabidopsis thaliana and Saccharomyces cerevisiae. The development and refinement of an affinity-enrichment strategy for unanchored polyubiquitin chains opens the way for more complete investigations into their biological significance. © 2013 Strachan J, et al

Mediator Acts Upstream of the Transcriptional Activator Gal4

We show that Mediator, a protein originally isolated on the basis of its ability to respond to transcriptional activators, and thought to be regulated by an activator, can also be the master that controls the activator

Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>A reverse engineering of gene regulatory network with large number of genes and limited number of experimental data points is a computationally challenging task. In particular, reverse engineering using linear systems is an underdetermined and ill conditioned problem, i.e. the amount of microarray data is limited and the solution is very sensitive to noise in the data. Therefore, the reverse engineering of gene regulatory networks with large number of genes and limited number of data points requires rigorous optimization algorithm.</p> <p>Results</p> <p>This study presents a novel algorithm for reverse engineering with linear systems. The proposed algorithm is a combination of the orthogonal least squares, second order derivative for network pruning, and Bayesian model comparison. In this study, the entire network is decomposed into a set of small networks that are defined as unit networks. The algorithm provides each unit network with P(D|H_i), which is used as confidence level. The unit network with higher P(D|H_i) has a higher confidence such that the unit network is correctly elucidated. Thus, the proposed algorithm is able to locate true positive interactions using P(D|H_i), which is a unique property of the proposed algorithm.</p> <p>The algorithm is evaluated with synthetic and <it>Saccharomyces cerevisiae </it>expression data using the dynamic Bayesian network. With synthetic data, it is shown that the performance of the algorithm depends on the number of genes, noise level, and the number of data points. With Yeast expression data, it is shown that there is remarkable number of known physical or genetic events among all interactions elucidated by the proposed algorithm.</p> <p>The performance of the algorithm is compared with Sparse Bayesian Learning algorithm using both synthetic and <it>Saccharomyces cerevisiae </it>expression data sets. The comparison experiments show that the algorithm produces sparser solutions with less false positives than Sparse Bayesian Learning algorithm.</p> <p>Conclusion</p> <p>From our evaluation experiments, we draw the conclusion as follows: 1) Simulation results show that the algorithm can be used to elucidate gene regulatory networks using limited number of experimental data points. 2) Simulation results also show that the algorithm is able to handle the problem with noisy data. 3) The experiment with Yeast expression data shows that the proposed algorithm reliably elucidates known physical or genetic events. 4) The comparison experiments show that the algorithm more efficiently performs than Sparse Bayesian Learning algorithm with noisy and limited number of data.</p

Emergence of 3D Printed Dosage Forms: Opportunities and Challenges

The recent introduction of the first FDA approved 3D-printed drug has fuelled interest in 3D printing technology, which is set to revolutionize healthcare. Since its initial use, this rapid prototyping (RP) technology has evolved to such as extent that it is currently being used in a wide range of applications including in tissue engineering, dentistry, construction, automotive and aerospace. However, in the pharmaceutical industry this technology is still in its infancy and its potential yet to be fully explored. This paper presents various 3D printing technologies such as stereolithographic, powder based, selective laser sintering, fused deposition modelling and semi-solid extrusion 3D printing. It also provides a comprehensive review of previous attempts at using 3D printing technologies on the manufacturing dosage forms with a particular focus on oral tablets. Their advantages particularly with adaptability in the pharmaceutical field have been highlighted, including design flexibility and control and manufacture which enables the preparation of dosage forms with complex designs and geometries, multiple actives and tailored release profiles. An insight into the technical challenges facing the different 3D printing technologies such as the formulation and processing parameters is provided. Light is also shed on the different regulatory challenges that need to be overcome for 3D printing to fulfil its real potential in the pharmaceutical industry

Multisite Phosphorylation Provides an Effective and Flexible Mechanism for Switch-Like Protein Degradation

Phosphorylation-triggered degradation is a common strategy for elimination of regulatory proteins in many important cell signaling processes. Interesting examples include cyclin-dependent kinase inhibitors such as p27 in human and Sic1 in yeast, which play crucial roles during the G1/S transition in the cell cycle. In this work, we have modeled and analyzed the dynamics of multisite-phosphorylation-triggered protein degradation systematically. Inspired by experimental observations on the Sic1 protein and a previous intriguing theoretical conjecture, we develop a model to examine in detail the degradation dynamics of a protein featuring multiple phosphorylation sites and a threshold site number for elimination in response to a kinase signal. Our model explains the role of multiple phosphorylation sites, compared to a single site, in the regulation of protein degradation. A single-site protein cannot convert a graded input of kinase increase to much sharper output, whereas multisite phosphorylation is capable of generating a highly switch-like temporal profile of the substrate protein with two characteristics: a temporal threshold and rapid decrease beyond the threshold. We introduce a measure termed temporal response coefficient to quantify the extent to which a response in the time domain is switch-like and further investigate how this property is determined by various factors including the kinase input, the total number of sites, the threshold site number for elimination, the order of phosphorylation, the kinetic parameters, and site preference. Some interesting and experimentally verifiable predictions include that the non-degradable fraction of the substrate protein exhibits a more switch-like temporal profile; a sequential system is more switch-like, while a random system has the advantage of increased robustness; all the parameters, including the total number of sites, the threshold site number for elimination and the kinetic parameters synergistically determine the exact extent to which the degradation profile is switch-like. Our results suggest design principles for protein degradation switches which might be a widespread mechanism for precise regulation of cellular processes such as cell cycle progression

Malaria parasites regulate the duration of the intra-erythrocytic cycle via serpentine receptor 10 and coordinate development with host daily rhythms

Malaria parasites complete their intra-erythrocytic developmental cycle (IDC) in multiples of 24 h suggesting a circadian basis, but the mechanism controlling this periodicity is unknown. Combining in vivo and in vitro approaches utilizing rodent and human malaria parasites, we reveal that: (i) 57% of Plasmodium chabaudi genes exhibit daily rhythms in transcription; (ii) 58% of these genes lose transcriptional rhythmicity when the IDC is out-of-synchrony with host rhythms; (iii) 6% of Plasmodium falciparum genes show 24 h rhythms in expression under free-running conditions; (iv) Serpentine receptor 10 (SR10) has a 24 h transcriptional rhythm and disrupting it in rodent malaria parasites shortens the IDC by 2-3 h; (v) Multiple processes including DNA replication, and the ubiquitin and proteasome pathways, are affected by loss of coordination with host rhythms and by disruption of SR10. Our results reveal malaria parasites are at least partly responsible for scheduling the IDC and coordinating their development with host daily rhythms

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome

Yeast IME2 Functions Early in Meiosis Upstream of Cell Cycle-Regulated SBF and MBF Targets

BACKGROUND: In Saccharomyces cerevisiae, the G1 cyclin/cyclin-dependent kinase (CDK) complexes Cln1,-2,-3/Cdk1 promote S phase entry during the mitotic cell cycle but do not function during meiosis. It has been proposed that the meiosis-specific protein kinase Ime2, which is required for normal timing of pre-meiotic DNA replication, is equivalent to Cln1,-2/Cdk1. These two CDK complexes directly catalyze phosphorylation of the B-type cyclin/CDK inhibitor Sic1 during the cell cycle to enable its destruction. As a result, Clb5,-6/Cdk1 become activated and facilitate initiation of DNA replication. While Ime2 is required for Sic1 destruction during meiosis, evidence now suggests that Ime2 does not directly catalyze Sic1 phosphorylation to target it for destabilization as Cln1,-2/Cdk1 do during the cell cycle. METHODOLOGY/PRINCIPAL FINDINGS: We demonstrated that Sic1 is eventually degraded in meiotic cells lacking the IME2 gene (ime2Δ), supporting an indirect role of Ime2 in Sic1 destruction. We further examined global RNA expression comparing wild type and ime2Δ cells. Analysis of these expression data has provided evidence that Ime2 is required early in meiosis for normal transcription of many genes that are also periodically expressed during late G1 of the cell cycle. CONCLUSIONS/SIGNIFICANCE: Our results place Ime2 at a position in the early meiotic pathway that lies upstream of the position occupied by Cln1,-2/Cdk1 in the analogous cell cycle pathway. Thus, Ime2 may functionally resemble Cln3/Cdk1 in promoting S phase entry, or it could play a role even further upstream in the corresponding meiotic cascade

Noise Cancellation: Viral Fine Tuning of the Cellular Environment for Its Own Genome Replication

Productive replication of DNA viruses elicits host cell DNA damage responses, which cause both beneficial and detrimental effects on viral replication. In response to the viral productive replication, host cells attempt to attenuate the S-phase cyclin-dependent kinase (CDK) activities to inhibit viral replication. However, accumulating evidence regarding interactions between viral factors and cellular signaling molecules indicate that viruses utilize them and selectively block the downstream signaling pathways that lead to attenuation of the high S-phase CDK activities required for viral replication. In this review, we describe the sophisticated strategy of Epstein-Barr virus to cancel such “noisy” host defense signals in order to hijack the cellular environment