Evaluation of biological protein-based collagen scaffolds in cartilage and musculoskeletal tissue engineering--a systematic review of the literature

The term tissue engineering is the technology that combines cells, engineering and biological/synthetic material in order to repair, replace or regenerate biological tissues such as bone, muscle, tendons and cartilage. The major human applications of tissue engineering are: skin, bone, cartilage, corneas, blood vessels, left mainstem bronchus and urinary structures. In this systematic review several criteria were identified as the most desirable characteristics of an ideal scaffold. These state that an ideal scaffolds needs to be biodegradable, possess mechanical strength, be highly porous, biocompatible, non-cytotoxic, non antigentic, stuitable for cell attachment, proliferation and differentiation, flexible and elastic, three dimensional, osteoconductive and support the transport of nutrients and metabolic waste. Subsequently, studies reporting on the various advantages and disadvantages of using collagen based scaffolds in musculoskeletal and cartilage tissue engineering were identified. The purpose of this review is to 1) provide a list of ideal characteristics of a scaffold as identified in the literature 2) identify different types of biological protein-based collagen scaffolds used in musculoskeletal and cartilage tissue engineering 3) assess how many of the criteria each scaffold type meets 4) weigh different scaffolds against each other according to their relative properties and shortcomings. The rationale behind this approach is that the ideal scaffold material has not yet been identified. Hence, this review will define how many of the identified ideal characteristics are fulfilled by natural collagen-based scaffolds and address the shortcomings of its use as found in the literature.     

Determining protein–protein functional associations by functional rules based on gene ontology and KEGG pathway

Protein–protein interactions (PPIs) describe the direct physical contact of two proteins that usually results in specific biological functions or regulatory processes. The characterization and study of PPIs through the investigation of their pattern and principle have remained a question in biological studies. Various experimental and computational methods have been used for PPI studies, but most of them are based on the sequence similarity with current validated PPI participators or cellular localization patterns. Most methods ignore the fact that PPIs are defined by their specific biological functions. In this study, we constructed a novel rule-based computational method using gene ontology and KEGG pathway annotation of PPI participators that correspond to the complicated biological effects of PPIs. Our newly presented computational method identified a group of biological functions that are tightly associated with PPIs and provided a new function-based tool for PPI studies in a rule manner.     

Osmosis; ATP; Process-based approach

The teaching of r and K population strategies involves integrating biological, graphical, and mathematical concepts so that a complex ‘concept image’ is formed. This investigation identified the main problems encountered by students in studying this topic as being interpreting graphs, making links with biological processes, and drawing general conclusions from data. The use of a formal lecture and three approaches to using a spreadsheet are evaluated, and suggestions are made for effective teaching of these concepts.     

An application of MeSH enrichment analysis in livestock

An integral part of functional genomics studies is to assess the enrichment of specific biological terms in lists of genes found to be playing an important role in biological phenomena. Contrasting the observed frequency of annotated terms with those of the background is at the core of overrepresentation analysis (ORA). Gene Ontology (GO) is a means to consistently classify and annotate gene products and has become a mainstay in ORA. Alternatively, Medical Subject Headings (MeSH) offers a comprehensive life science vocabulary including additional categories that are not covered by GO. Although MeSH is applied predominantly in human and model organism research, its full potential in livestock genetics is yet to be explored. In this study, MeSH ORA was evaluated to discern biological properties of identified genes and contrast them with the results obtained from GO enrichment analysis. Three published datasets were employed for this purpose, representing a gene expression study in dairy cattle, the use of SNPs for genome‐wide prediction in swine and the identification of genomic regions targeted by selection in horses. We found that several overrepresented MeSH annotations linked to these gene sets share similar concepts with those of GO terms. Moreover, MeSH yielded unique annotations, which are not directly provided by GO terms, suggesting that MeSH has the potential to refine and enrich the representation of biological knowledge. We demonstrated that MeSH can be regarded as another choice of annotation to draw biological inferences from genes identified via experimental analyses. When used in combination with GO terms, our results indicate that MeSH can enhance our functional interpretations for specific biological conditions or the genetic basis of complex traits in livestock species.     

Character identification in evolutionary biology: The role of the organism

Summary In this article we argue that an organismic perspective in character identification can alleviate a structural deficiency of mathematical models in biology relative to the ones in the physical sciences. The problem with many biological theories is that they do not contain the conditions of their validity or a method of identifying objects that are appropriate instances of the models. Here functionally important biological characters are introduced as conceptual abstractions derived within the context of an ontologically prior object, such as a cell or an organism. To illustrate this approach, we present an analytical method of character decomposition based on the notion of the quasi-independence of traits. Two cases are analyzed: context dependent units of inheritance and a model of character identification in adaptive evolution. We demonstrate that in each case the biological process as represented by a mathematical theory entails the conditions for the individualization of characters. Our approach also requires a conceptual re-orientation in the way we build biological models. Rather than defining a set of biological characters a priori, functionally relevant characters are identified in the context of a higher level biological process.     

Progress in risk assessment for classical biological control

There has been considerable debate on risks associated with biological control, and partly resulting from this, research has addressed a number of questions which have subsequently led to a greater understanding of risk assessment and biosafety. Controversy which arose in the 1980s about the environmental safety of biological control initially created considerable tension between biological control practitioners and those concerned about non-target impacts. Several factors have helped to ease this pressure, and a substantial body of research has addressed many of the questions raised. This has led to advances in quarantine laboratory host range testing to improve our ability to predict post-release impacts. Furthermore, pre- and post-release studies are increasingly involving population models to estimate the population impact of introduced biological control agents rather than simply measuring attack rates. Regulators making decisions about biological control agent introductions work under conditions of considerable uncertainty, but with accumulating data from past introductions to validate earlier decisions, and a robust peer review system for assessing new proposals, there is cause for some optimism that the risks associated with biological control can be better identified and managed in the future. Progress in research and regulation of biological control are discussed with particular reference to Australasia.     

GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)

Background  

The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as "unknowns".     

A critical assessment of storytelling: gene ontology categories and the importance of validating genomic scans

In the age of whole-genome population genetics, so-called genomic scan studies often conclude with a long list of putatively selected loci. These lists are then further scrutinized to annotate these regions by gene function, corresponding biological processes, expression levels, or gene networks. Such annotations are often used to assess and/or verify the validity of the genome scan and the statistical methods that have been used to perform the analyses. Furthermore, these results are frequently considered to validate "true-positives" if the identified regions make biological sense a posteriori. Here, we show that this approach can be potentially misleading. By simulating neutral evolutionary histories, we demonstrate that it is possible not only to obtain an extremely high false-positive rate but also to make biological sense out of the false-positives and construct a sensible biological narrative. Results are compared with a recent polymorphism data set from Drosophila melanogaster.     

Introducing Dynamics into the Field of Biosemiotics

Coding plays a universal and pervasive role in biological organization, in forms such as genetic coding (DNA to protein translation), RNA processing, gene regulation, protein modification, cell signalling, immune responses, epigenetic development and natural language. Nevertheless, the ways and means by which organic codes are formed and used are still poorly understood. A formal model is presented in this paper to investigate the emergence of conventional codes among code users. The relationship between the formation and the usage of codes is discussed, and a biological mechanism involving coding is identified in the context of the immune system.     

Mechanisms of type-I interferon signal transduction

Interferons regulate a number of biological functions including control of cell proliferation, generation of antiviral activities and immumodulation in human cells. Studies by several investigators have identified a number of cellular signaling cascades that are activated during engagement of interferon receptors. The activation of multiple signaling cascades by the interferon receptors appears to be critical for the generation of interferon-mediated biological functions and immune surveillance. The present review summarizes the existing knowledge on the multiple signaling cascades activated by Type I interferons. Recent developments in this research area are emphasized and the implications of these new discoveries on our understanding of interferon actions are discussed.     

Analysis of connection networks among miRNAs differentially expressed in early gastric cancer for disclosing some biological features of disease development

This paper first identified differentially expressed miRNAs associated with early gastric cancer and then respectively constructed relevant connection networks among the identified differentially expressed miRNAs that corresponded to early gastric cancer and control tissues. Twenty-three differentially expressed miRNAs were identified, 18 of which were different with the related results on the same data, and they provide great discriminatory power between patients and controls. There are not only conserved unchangeable sub-networks but also different sub-networks between the two connection networks. From the consistency and differences between two connection networks, we disclosed several new biological features that promote early gastric cancer development. This study shows 23 miRNAs that are early gastric cancer-specific and are worthy to do further experimental studies. The revealed biological features for early gastric cancer will provide new insights into improved understanding of the molecular mechanisms of this disease.     

Physical anthropology,peace and justice: Some observations

Human biological well being is a concern of physical anthropology. Genetic determinants and also sociocultural factors, which operate through biological bases, affect human biological quality. Several populations from different parts of the globe have been identified where varieties of detrimental genes occur in considerable numbers influencing health and some other related biological aspects of human life. Injustice will be done to those populations if necessary measures are not undertaken to improve their biological qualities. Peace cannot prevail in an atmosphere where people are deprived of the basic amenities for survival and maintenance of good health.     

Identifying responsive modules by mathematical programming: an application to budding yeast cell cycle

High-throughput biological data offer an unprecedented opportunity to fully characterize biological processes. However, how to extract meaningful biological information from these datasets is a significant challenge. Recently, pathway-based analysis has gained much progress in identifying biomarkers for some phenotypes. Nevertheless, these so-called pathway-based methods are mainly individual-gene-based or molecule-complex-based analyses. In this paper, we developed a novel module-based method to reveal causal or dependent relations between network modules and biological phenotypes by integrating both gene expression data and protein-protein interaction network. Specifically, we first formulated the identification problem of the responsive modules underlying biological phenotypes as a mathematical programming model by exploiting phenotype difference, which can also be viewed as a multi-classification problem. Then, we applied it to study cell-cycle process of budding yeast from microarray data based on our biological experiments, and identified important phenotype- and transition-based responsive modules for different stages of cell-cycle process. The resulting responsive modules provide new insight into the regulation mechanisms of cell-cycle process from a network viewpoint. Moreover, the identification of transition modules provides a new way to study dynamical processes at a functional module level. In particular, we found that the dysfunction of a well-known module and two new modules may directly result in cell cycle arresting at S phase. In addition to our biological experiments, the identified responsive modules were also validated by two independent datasets on budding yeast cell cycle.     

Acetylenic aromatic compounds from Stereum hirsutum

Stereum hirsutum is a one of several fungi involved in a grapevine disease called esca. From the culture medium of this fungus, four new acetylenic compounds 1-3 and 6 have been isolated and identified. Structural elucidation and biological activity are reported.     

Characterization of bioactive glycolipids from Scytonema julianum (cyanobacteria)

Cyanobacteria serve as a rich source of novel bioactive metabolites. Few studies on glycolipids reported them as having specific biological activities. In this study, total lipids of Scytonema julianum, a filamentous cyanobacterium isolated from a Greek cave, were separated into neutral and phospho- and glycolipids, and the latter were further fractionated by high-performance liquid chromatography (HPLC). Each glycolipid fraction was tested in vitro for its ability to inhibit platelet-activating factor (PAF)- and thrombin-induced washed rabbit platelet aggregation and/or to cause platelet aggregation. The structures of the most active fractions were elucidated by biological assays, by chemical determinations and identified by electrospray mass spectrometry. One fraction was a potent inhibitor of PAF-induced platelet aggregation. Structural studies of this fraction indicated the existence of a phosphoglyco-analog of acyl-sphingosine. Two fractions causing platelet aggregation were detected and identified as phosphoglycolipids. The first one was identified as a phosphoglyco-analog of acyl-acetylated sphingosine and the second one as a glyco-analog of phosphatidylglycerol. The presence of the above bioactive compounds demonstrates new types of lipids in cyanobacteria in regard to the structure and biological activity. In addition, the identified bioactive lipids may contribute to the allergic character of cyanobacteria.