Metabolic networks classification and knowledge discovery by information granulation.

Graphs are powerful structures able to capture topological and semantic information from data, hence suitable for modelling a plethora of real-world (complex) systems. For this reason, graph-based pattern recognition gained a lot of attention in recent years. In this paper, a general-purpose classification system in the graphs domain is presented. When most of the information of the available patterns can be encoded in edge labels, an information granulation-based approach is highly discriminant and allows for the identification of semantically meaningful edges. The proposed classification system has been tested on the entire set of organisms (5299) for which metabolic networks are known, allowing for both a perfect mirroring of the underlying taxonomy and the identification of most discriminant metabolic reactions and pathways. The widespread diffusion of graph (network) structures in biology makes the proposed pattern recognition approach potentially very useful in many different fields of application. More specifically, the possibility to have a reliable metric to compare different metabolic systems is instrumental in emerging fields like microbiome analysis and, more in general, for proposing metabolic networks as a universal phenotype spanning the entire tree of life and in direct contact with environmental cues.

Big Data. A briefing.

The data deluge (generally referred as "Big Data") biomedical scientists are facing in these years asks for a serious epistemological thinking in order to avoid both "data bases idolatry" and "preconceived refusal". Starting from the evident reproducibility crisis of biomedical sciences here we sketch some hopefully useful indications for a sensible use of data mining approaches.

Microcalcification morphological descriptors and parenchyma fractal dimension hierarchically interact in breast cancer: A diagnostic perspective.

INTRODUCTION: Herein, we propose a Systems Biology approach aimed at identifying quantitative morphological parameters useful in discriminating benign from malignant breast microcalcifications at digital mammography. MATERIALS AND METHODS: The study includes 31 patients in which microcalcifications had been detected during XR mammography and were further confirmed by stereotactic (XR-guided) biopsies. Patients were classified according to the BIRADS (Breast Imaging-Reporting and Data System), along with their parenchyma fractal dimension and biopsy size. A geometrical-topological characterization of microcalcifications was obtained as well. RESULTS: The 'size of biopsy' was the parameter endowed with the highest discriminant power between malignant and benign lesions thus confirming the reliability of surgeon judgment. The quantitative shape evaluation of both lesions and parenchyma allowed for a promising prediction of the BIRADS score. The area of lesions and parenchyma fractal dimension show a complex distribution for malignant breast calcifications that are consistent with their qualitative morphological pattern. Fractal dimension analysis enables the user to obtain reliable results as proved by its efficiency in the prediction of the morphology of breast cancer. CONCLUSION: By reconstructing a phase-space distribution of biophysical parameters, different patterns of aggregation are recognized corresponding to different calcium deposition patterns, while the combination of tissue and microcalcification morphological descriptors provide a statistically significant prediction of tumour grade. CLINICAL RELEVANCE: The development of an automated morphology evaluation system can help during clinical evaluation while also sketching mechanistic hypotheses of microcalcification generation.

Lipid droplet autophagy in the yeast Saccharomyces cerevisiae.

Cytosolic lipid droplets (LDs) are ubiquitous organelles in prokaryotes and eukaryotes that play a key role in cellular and organismal lipid homeostasis. Triacylglycerols (TAGs) and steryl esters, which are stored in LDs, are typically mobilized in growing cells or upon hormonal stimulation by LD-associated lipases and steryl ester hydrolases. Here we show that in the yeast Saccharomyces cerevisiae, LDs can also be turned over in vacuoles/lysosomes by a process that morphologically resembles microautophagy. A distinct set of proteins involved in LD autophagy is identified, which includes the core autophagic machinery but not Atg11 or Atg20. Thus LD autophagy is distinct from endoplasmic reticulum-autophagy, pexophagy, or mitophagy, despite the close association between these organelles. Atg15 is responsible for TAG breakdown in vacuoles and is required to support growth when de novo fatty acid synthesis is compromised. Furthermore, none of the core autophagy proteins, including Atg1 and Atg8, is required for LD formation in yeast.

Autophagy: principles and significance in health and disease.

Degradation processes are important for optimal functioning of eukaryotic cells. The two major protein degradation pathways in eukaryotes are the ubiquitin-proteasome pathway and autophagy. This contribution focuses on autophagy. This process is important for survival of cells during nitrogen starvation conditions but also has a house keeping function in removing exhausted, redundant or unwanted cellular components. We present an overview of the molecular mechanism involved in three major autophagy pathways: chaperone mediated autophagy, microautophagy and macroautophagy. Various recent reports indicate that autophagy plays a crucial role in human health and disease. Examples are presented of lysosomal storage diseases and the role of autophagy in cancer, neurodegenerative diseases, defense against pathogens and cell death.

Pex14p is not required for N-starvation induced microautophagy and in catalytic amounts for macropexophagy in Hansenula polymorpha.

We showed before that the two oppositely directed processes of peroxisome biogenesis and selective peroxisome degradation (macropexophagy) converge at the peroxisomal membrane protein Pex14p. Here we show that this protein is not required for peroxisome degradation during nitrogen starvation-induced general autophagy, thereby limiting its function to the selective degradation process. Pex14p is present in two forms, namely an unmodified (Pex14p) and a phosphorylated form (Pex14p(Pi)) that are differently induced during peroxisome proliferation. The data suggest that Pex14p is required for peroxisome biogenesis during organelle proliferation and Pex14p(Pi) in macropexophagy. Finally, we show that macropexophagy is not coupled to normal peroxisome assembly, because Pex14p is required in only catalytic amounts to allow initiation of the selective peroxisome degradation process.