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The Human Genome Project has deeply transformed biology and the field has since then expanded to the management, processing, analysis and visualization of large quantities of data from genomics, proteomics, medicinal chemistry and drug screening. This huge amount of data and the heterogeneity of software tools that are used implies the adoption on a very large scale of new, flexible tools that can enable researchers to integrate data and analysis on the network. ICT technology standards and tools, like Web Services and related languages, and workflow management systems, can support the creation and deployment of such systems. While a number of Web Services are appearing and personal workflow management systems are also being more and more offered to researchers, a reference portal enabling the vast majority of unskilled researchers to take profit from these new technologies is still lacking. In this paper, we introduce the rationale for the creation of such a portal and present the architecture and some preliminary results for the development of a portal for the enactment of workflows of interest in oncology.

This paper describes current theoretical work in a cognitive anthropological approach to the analysis of oral literature. A theory of narrative grammar is presented along with the description of a computer program, SAGE, that is currently under development. SAGE facilitates the labelling of clauses and sentences by different types of semantic features. It maps and counts the occurrences of these in the stories analyzed. © 1991 Human Sciences Press, Inc.

Flood risk assessment and mitigation are important tasks that should take advantage of rational vulnerability models to increase their effectiveness. These models are usually identified through a relevant set of laboratory experiments. However, there is growing evidence that these tests are not fully representative of the variety of conditions that characterize real flood hazard situations. This paper suggests a citizen science-based and innovative approach to obtain information from web resources for the calibration of people's vulnerability models. A comprehensive study employing commonly used web engines allowed the collection of a wide set of documents showing real risk situations for people impacted by floods, classified according to the stability of the involved subjects. A procedure to extrapolate the flow depth and velocity from the video frames is developed and its reliability is verified by comparing the results with observation. The procedure is based on the statistical distribution of the population height employing a direct uncertainty propagation method. The results complement the experimental literature data and conceptual models. The growing availability of online information will progressively increase the sample size on which the procedure is based and will eventually lead to the identification of a probability surface describing the transition between stability and instability conditions of individuals in a flow. [ABSTRACT FROM AUTHOR]

The role of dysbiosis causing leaky gut with xenobiotic production and absorption is increasingly demonstrated in autism spectrum disorder (ASD) pathogenesis. Among xenobiotics, we focused on ochratoxin A (one of the major food contaminating mycotoxin), that in vitro and in vivo exerts a male-specific neurotoxicity probably via microRNA modulation of a specific target gene. Among possible targets, we focused on neuroligin4X. Interestingly, this gene carries some single nucleotide polymorphisms (SNPs) already correlated with the disease and with illegitimate microRNA binding sites and, being located on X-chromosome, could explain the male prevalence. In conclusion, we propose a possible gene-environment interaction triggering ASD explaining the epigenetic neurotoxic mechanism activated by ochratoxin A in genetically predisposed children. This mechanism offers a clue for male prevalence of the disease and may have an important impact on prevention and cure of ASD. [ABSTRACT FROM AUTHOR]

Background Two mutations in the MYBPC3 gene have been identified in Maine Coon ( MCO) and Ragdoll ( RD) cats with hypertrophic cardiomyopathy ( HCM). Objective This study examined the frequency of these mutations and of the A74T polymorphism to describe their worldwide distribution and correlation with echocardiography. Animals: 1855 cats representing 28 breeds and random-bred cats worldwide, of which 446 underwent echocardiographic examination. Methods This is a prospective cross-sectional study. Polymorphisms were genotyped by Illumina VeraCode GoldenGate or by direct sequencing. The disease status was defined by echocardiography according to established guidelines. Odds ratios for the joint probability of having HCM and the alleles were calculated by meta-analysis. Functional analysis was simulated. Results The MYBPC3 A31P and R820W were restricted to MCO and RD, respectively. Both purebred and random-bred cats had HCM and the incidence increased with age. The A74T polymorphism was not associated with any phenotype. HCM was most prevalent in MCO homozygote for the A31P mutation and the penetrance increased with age. The penetrance of the heterozygote genotype was lower (0.08) compared with the P/P genotype (0.58) in MCO. Conclusions and Clinical Importance A31P mutation occurs frequently in MCO cats. The high incidence of HCM in homozygotes for the mutation supports the causal nature of the A31P mutation. Penetrance is incomplete for heterozygotes at A31P locus, at least at a young age. The A74T variant does not appear to be correlated with HCM. [ABSTRACT FROM AUTHOR]

Background: Inflammatory bowel diseases (IBD) refer to a group of inflammatory conditions concerning colon and small intestine, which cause socially uncomfortable symptoms and often are associated with an increased risk of colon cancer. IBD are complex disorders, which rely on genetic susceptibility, environmental factors, deregulation of the immune system, and host relationship with commensal microbiota. The complexity of these pathologies makes difficult to clearly understand the mechanisms of their onset. Therefore, the study of IBD must be faced exploiting an integrated and multilevel approach, ranging from genes, transcripts and proteins to pathways altered in affected tissues, and carefully considering their regulatory mechanisms, which may intervene in the pathology onset. It is also crucial to have a knowledge base about the symbiotic bacteria that are hosted in the human gut. To date, much data exist regarding IBD and human commensal bacteria, but this information is sparse in literature and no free resource provides a homogeneously and rationally integrated view of biomolecular data related to these pathologies. Methods: Human genes altered in IBD have been collected from literature, paying particular interest for the immune system alterations prompted by the interaction with the gut microbiome. This process has been performed manually to assure the reliability of collected data. Heterogeneous metadata from different sources have been automatically formatted and integrated in order to enrich information about these altered genes. A userfriendly web interface has been created for easy access to structured data. Tools such as gene clustering coefficients, all-pairs shortest paths and pathway lengths calculation have been developed to provide data analysis support. Moreover, the implemented resource is compliant to the Galaxy framework, allowing the collected data to be exploited in the context of high throughput bioinformatics analysis. Results: To fill the lack of a reference resource for 'omics' science analysis in the context of IBD, we developed the IBDsite (available at http://www.itb.cnr.it/ibd), a disease-oriented platform, which collects data related to biomolecular mechanisms involved in the IBD onset. The resource provides a section devoted to human genes identified as altered in IBD, which can be queried at different biomolecular levels and visualised in gene-centred report pages. Furthermore, the system presents information related to the gut microbiota involved in IBD affected patients. The IBDsite is compliant with all Galaxy installations (in particular, it can be accessed from our custom version of Galaxy, http://www.itb.cnr.it/galaxy), in order to facilitate high-throughput data integration and to enable evaluations of the genomic basis of these diseases, complementing the tools embedded in the IBDsite. Conclusions: Lots of sparse data exist concerning IBD studies, but no on-line resource homogeneously and rationally integrate and collect them. The IBDsite is an attempt to group available information regarding human genes and microbial aspects related to IBD, by means of a multilevel mining tool. Moreover, it constitutes a knowledge base to filter, annotate and understand new experimental data in order to formulate new scientific hypotheses, thanks to the possibility of integrating genomics aspects by employing the Galaxy framework. Discussed use-cases demonstrate that the developed system is useful to infer not trivial knowledge from the existing widespread data or from novel experiments [ABSTRACT FROM AUTHOR]

Grid technology and ICT-based infrastructures play a crucial role in the development of transnational multi-disciplinary collaborations and allow scientists to share a wide range of distributed computational resources, regardless of their geographical location, and address new global scientific challenges. Till now, the strict security policy requested in order to access distributed computing resources has been a limiting factor when trying to broaden the adoption of Grids by wide communities of users. There is a steep learning curve to climb before starting to gain some benefits from this new technology. Grid security is indeed based on the Public Key Infrastructure (PKI) of X.509 certificate although the procedure to get and manage those certificates is unfortunately not straightforward. A first step to make Grids more appealing for new users has recently been achieved with the adoption of robot certificates. In this paper, the solution proposed by the Italian National Institute of Nuclear Physics to go through the complexity of Grid security and allow bioinformaticians to perform large-scale Bayesian Phylogenetic analyses on the Grid by means of a web portal enabled by a robot certificate is presented. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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There is little known about how, or whether, GA3 affects development of lentils (Lens culinaris Medikus subsp. culinaris). In the field, lentil was treated at two times with four concentrations of GA3 and with or without irrigation. Concentration of GA3 affected plant height, numbers of branches and pods, 100 seed weight, and yield. The 10 mg·L-1 concentration of GA3 resulted in increased yield and increased percentage of pods with two seeds. The 50 mg·L-1 concentration of GA3 produced more branches. Application of GA3 at flowering increased yield by 60%. Irrigation produced the greatest number of pods and the highest yield. Lentil production can be increased by applying concentrations of GA3 between 10 and 50 mg·L-1 at flowering. [ABSTRACT FROM AUTHOR]

Molecular dynamics is very important for biomedical research because it makes possible simulation of the behavior of a biological macromolecule in silico. However, molecular dynamics is computationally rather expensive: the simulation of some nanoseconds of dynamics for a large macromolecule such as a protein takes very long time, due to the high number of operations that are needed for solving the Newton's equations in the case of a system of thousands of atoms. In order to obtain biologically significant data, it is desirable to use high-performance computation resources to perform these simulations. Recently, a distributed computing approach based on replacing a single long simulation with many independent short trajectories has been introduced, which in many cases provides valuable results. This study concerns the development of an infrastructure to run molecular dynamics simulations on a grid platform in a distributed way. The implemented software allows the parallel submission of different simulations that are singularly short but together bring important biological information. Moreover, each simulation is divided into a chain of jobs to avoid data loss in case of system failure and to contain the dimension of each data transfer from the grid. The results confirm that the distributed approach on grid computing is particularly suitable for molecular dynamics simulations thanks to the elevated scalability. [ABSTRACT FROM PUBLISHER]

We address the problem of finding large-scale functional and structural relationships between genes, given a time series of gene expression data, namely mRNA concentration values measured from genetically engineered rat fibroblasts cell lines responding to conditional cMyc proto-oncogene activation. We show how it is possible to retrieve suitable information about molecular mechanisms governing the cell response to conditional perturbations. This task is complex because typical high-throughput genomics experiments are performed with high number of probesets (103–104 genes) and a limited number of observations (< 102 time points). In this paper, we develop a deepest analysis of our previous work [Remondini et al., 2005] in which we characterized some of the main features of a gene-gene interaction network reconstructed from temporal correlation of gene expression time series. One first advancement is based on the comparison of the reconstructed network with networks obtained from randomly generated data, in order to characterize which features retrieve real biological information, and which are instead due to the characteristics of the network reconstruction method. The second and perhaps more relevant advancement is the characterization of the global change in co-expression pattern following cMyc activation as compared to a basal unperturbed state. We propose an analogy with a physical system in a critical state close to a phase transition (e.g. Potts ferromagnet), since the cell responds to the stimulus with high susceptibility, such that a single gene activation propagates to almost the entire genome. Our result is relative to temporal properties of gene network dynamics, and there are experimental evidence that this can be related to spatial properties regarding the global organization of chromatine structure [Knoepfler et al., 2006]. [ABSTRACT FROM AUTHOR]

The identification of the genes that are coordinately regulated is an important and challenging task of bioinformatics and represents a first step in the elucidation of the topology of transcriptional networks. We first compare the performances, in a grid setting, of the Markov clustering algorithm with respect to the k-means using microarray test data sets. The gene expression information of the clustered genes can be used to annotate transcription binding sites upstream co-regulated genes. The methodology uses a regression model that relates gene expression levels to the matching scores of nucleotide patterns allowing us to identify DNA-binding sites from a collection of noncoding DNA sequences from co-regulated genes. Here we discuss extending the approach to multiple species exploiting the grid framework. [ABSTRACT FROM PUBLISHER]

Bioinformatic tools are often used by researchers through interactive Web interfaces, resulting in a strong demand for computational resources. The tools are of different kind and range from simple, quick tasks, to complex analyses requiring minutes to hours of processing time and often longer than that. Batteries of computational nodes, such as those found in parallel clusters, provide a platform of choice for this application, especially when a relatively large number of concurrent requests is expected. Here, we describe a scheduling architecture operating at the application level, able to distribute jobs over a large number of hierarchically organized nodes. While not contrasting and peacefully living together with low-level scheduling software, the system takes advantage of tools, such as SQL servers, commonly used in Web applications, to produce low latency and performance which compares well and often surpasses that of more traditional, dedicated schedulers. The system provides the basic functionality necessary to node selection, task execution and service management and monitoring, and may combine loosely linked computational resources, such as those located in geographically distinct sites. [ABSTRACT FROM PUBLISHER]

Due to the huge volume and complexity of biological data available today, a fundamental component of biomedical research is now in silico analysis. This includes modelling and simulation of biological systems and processes, as well as automated bioinformatics analysis of high-throughput data. The quest for bioinformatics resources (including databases, tools, and knowledge) becomes therefore of extreme importance. Bioinformatics itself is in rapid evolution and dedicated Grid cyberinfrastructures already offer easier access and sharing of resources. Furthermore, the concept of the Grid is progressively interleaving with those of Web Services, semantics, and software agents. Agent-based systems can play a key role in learning, planning, interaction, and coordination. Agents constitute also a natural paradigm to engineer simulations of complex systems like the molecular ones. We present here an agent-based, multilayer architecture for bioinformatics Grids. It is intended to support both the execution of complex in silico experiments and the simulation of biological systems. In the architecture a pivotal role is assigned to an "alive" semantic index of resources, which is also expected to facilitate users' awareness of the bioinformatics domain. [ABSTRACT FROM PUBLISHER]

This paper reports on an analysis of the bioinformaties and medical informatics literature with the objective to identify upcoming trends that are shared among both research fields to derive benefits from potential collaborative initiatives for their future. Our results present the main characteristics of the two fields and show that these domains are still relatively separated. [ABSTRACT FROM AUTHOR]

Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) , the second data challenge battling avian flu was kicked off in April 2006 to identify new drugs for the potential variants of the influenza A virus. Mobilizing thousands of CPUs on the Grid, the six-week-long high-throughput screening activity has fulfilled over 100 CPU years of computing power and produced around 600 gigabytes of results on the Grid for further biological analysis and testing. In the paper, we demonstrate the impact of a worldwide Grid infrastructure to efficiently deploy large-scale virtual screening to speed up the drug design process. Lessons learned through the data challenge activity are also discussed [ABSTRACT FROM PUBLISHER]

Starting from the genomic and proteomic sequence data, a complex computational infrastructure as been established with the objective to develop a GRID based system to to automate the analysis, prediction and annotation processes of genomic DNA. To support of this type of analysis, several algorithms as been used to recognize biological signals involved in the identification of genes and proteins. The system implemented can be use to analyse the content of the large number of genomic sequences. For this reason, the system realized is capable of using a computational architecture specifically designed for intensive computing based on GRID technologies developed throughout the BIOINFOGRID European project. We developed a GRID based workflow to correlate different kind of Bioinformatics data, going from the Genomics Nucleotide to the Protein Sequence. The first step in the workflow consists of submitting a nucleotide sequence that is elaborated by a specific software for gene prediction. In particular this tool performs a search in the nucleotide sequence to find out the key components of gene. The predicted gene is then translated in the corresponding protein sequence. Based on protein sequence is then possible to identify the domains that characterize the protein functionality using specific tools of domain prediction. Protein domains classification are very important in the analysis of the macromolecular functionality. To analyze a whole protein family from large genome of various organism means to elaborate a large amount of data that requires huge computational resources. To analyze all this data we suggest the use of a high performance platform based on grid technology. We have implemented our applications on a wide area grid platform for scientific applications [http://www.grid.it and http://grid-it.cnaf.infn.it] composed of about 1000 CPU's. The grid infrastructure consists in a collection of computing elements and storage elements that jointly concur to define a platform for high performance elaboration. In this study a grid based application is presented to compute the protein domain analysis in a distributed way. This approach has high performance because the protein domains are checked with different software in parallel in different grid sites. [ABSTRACT FROM AUTHOR]

Surface characterization of peptides may provide useful information about functionality and potential interactions with other molecules. A description of a protein site through a surface that models the shape conferred by the exposed residues is an effective tool for the analysis and the modeling of proteins that may highlight similarities and relationships not detectable through comparisons at level of primary, secondary, and tertiary structure. This study concerns the development of a tool that extracts the residues that concur to the shape modeling of the surface of a protein or a portion of it. This task is accomplished without taking into account the order of the amino acids in the primary structure, but only according to the selection of a portion of the protein indicated through geometric parameters or an explicit list of amino acids belonging to the site of interest. Both in the case of an entire protein and in the case of a portion of it, the method provides the mesh that models the surface described by the exposed residues that constitute the external envelope. The developed tool which allows the extraction of the exposed residues, and thus of the potential function determinants, is applied to identify the amino acids that concur to the structural interaction in several protein complexes. [ABSTRACT FROM PUBLISHER]

It is well known that protein secondary-structure information can help the process of performing multiple alignment, in particular when the amount of similarity among the involved sequences moves toward the "twilight zone" (less than 30% of pairwise similarity). In this paper, a multiple alignment algorithm is presented, explicitly designed for exploiting any available secondary-structure information. A layered architecture with two interacting levels has been defined for dealing with both primary- and secondary-structure information of target sequences. Secondary structure (either available or predicted by resorting to a technique based on multiple experts) is used to calculate an initial alignment at the secondary level, to be arranged by locally scoped operators devised to refine the alignment at the primary level. Aimed at evaluating the impact of secondary information on the quality of alignments, in particular alignments with a low degree of similarity, the technique has been implemented and assessed on relevant test cases. [ABSTRACT FROM PUBLISHER]

The completion of a number of large genome sequencing projects emphasizes the importance of protein-coding gene predictions. Most of the problems associated with gene prediction are caused by the complex exon-intron structures commonly found in eukaryotic genomes. However, information from homologous sequences can significantly improve the accuracy of the prediction. In particular, expressed sequence tags (ESTs) are very useful for this purpose, since currently existing EST collections are very large. We developed an ESTMAP system, which utilizes homology searches against a database of repetitive elements using the RepeatView program and the EST Division of GenBank using the BLASTN program. ESTMAP extracts "exact" matches with EST sequences (>95% of homology) from BLASTN output file and predicts introns in DNA comparing ESTs and a query sequence. ESTMAP is implemented as a part of the WebGene system (http://www.cnr.it/webgene). [ABSTRACT FROM PUBLISHER]

The ten papers in this special section focus on grid, web services, software agents, and ontology applications for life sciences. While most of the papers focus on Grid and distributed computation, others are concerned with advanced techniques and methodologies, like Web services and agent-based systems. [ABSTRACT FROM PUBLISHER]

Here we report a detailed study of the interactions of nanoparticles, formed by the self-assembly of cholesterol-containing porphyrins, with lipid membranes. We show that the interaction is a two-step process: first, the docking and fusion, then, the redistribution of the building blocks of the self-assembled nanoparticles (SANs henceforth). Analysis of the binding and structural data is consistent with the docking step being driven by a multivalence cooperative effect and with the formation of SAN aggregates on the membrane, whilst the solubility of the cholesterol anchor in the membrane is key to both the fusion and redistribution of the SANs building blocks. The tendency of the SAN to aggregate in the membrane helps explain the photosensitizer properties of the SANs, essential to their anti-microbial activity. The solubility of the cholesteryl anchors drives fusion to the membrane and de-assembly of the SAN, explaining the capability of the SANs to deliver therapeutic cargos at the lipid interface. The subsequent redistribution of the SANs building blocks offer a plausible pathway to body clearance that is not immediately available to hard nanoparticles. These properties, and the modularity of the synthesis, point to the SANs being an excellent platform for the development of nanomedicines. An unexpected consequence of unraveling the mechanism of membrane interaction of these SANs is that it allows us to derive a value of the free energy of binding of cholesterol (the membrane anchor of the SAN building blocks) to a lipid membrane, that is consistent with the literature values. This is an additional property that can be exploited to determine the affinity of a variety of membrane anchors to membranes of various compositions., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Salvador Tomas reports financial support was provided by State Research Agency (Spain). Lilia Milanesi reports financial support was provided by State Research Agency (Spain). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Multiple sclerosis (MS) is a complex disorder characterized by high heterogeneity in terms of phenotypic expression, prognosis and treatment response. In the present study, we aimed to explore the genetic contribution to MS disease activity at different levels: genes, pathways and tissue-specific networks. Two cohorts of relapsing-remitting MS patients who started a first-line treatment (n = 1294) were enrolled to evaluate the genetic association with disease activity after 4 years of follow-up. The analyses were performed at whole-genome SNP and gene level, followed by the construction of gene-gene interaction networks specific for brain and lymphocytes. The resulting gene modules were evaluated to highlight key players from a topological and functional perspective. We identified 23 variants and 223 genes with suggestive association to 4-years disease activity, highlighting genes like PON2 involved in oxidative stress and in mitochondria functions and other genes, like ILRUN, involved in the modulation of the immune system. Network analyses led to the identification of a brain module composed of 228 genes and a lymphocytes module composed of 287 genes. The network analysis allowed us to prioritize genes relevant for their topological properties; among them, there are MPHOSPH9 (connector hub in both brain and lymphocyte module) and OPA1 (in brain module), two genes already implicated in MS. Modules showed the enrichment of both shared and tissue-specific pathways, mainly implicated in inflammation. In conclusion, our results suggest that the processes underlying disease activity act on shared mechanisms across brain and lymphocyte tissues., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

We recently identified TMEM230 as a master regulator of the endomembrane system of cells. TMEM230 expression is necessary for promoting motor protein dependent intracellular trafficking of metalloproteins for cellular energy production in mitochondria. TMEM230 is also required for transport and secretion of metalloproteinases for autophagy and phagosome dependent clearance of misfolded proteins, defective RNAs and damaged cells, activities that decline with aging. This suggests that aberrant levels of TMEM230 may contribute to aging and regain of proper levels may have therapeutic applications. The components of the endomembrane system include the Golgi complex, other membrane bound organelles, and secreted vesicles and factors. Secreted cellular components modulate immune response and tissue regeneration in aging. Upregulation of intracellular packaging, trafficking and secretion of endosome components while necessary for tissue homeostasis and normal wound healing, also promote secretion of pro-inflammatory and pro-senescence factors. We recently determined that TMEM230 is co-regulated with trafficked cargo of the endomembrane system, including lysosome factors such as RNASET2. Normal tissue regeneration (in aging), repair (following injury) and aberrant destructive tissue remodeling (in cancer or autoimmunity) likely are regulated by TMEM230 activities of the endomembrane system, mitochondria and autophagosomes. The role of TMEM230 in aging is supported by its ability to regulate the pro-inflammatory secretome and senescence-associated secretory phenotype in tissue cells of patients with advanced age and chronic disease. Identifying secreted factors regulated by TMEM230 in young patients and patients of advanced age will facilitate identification of aging associated targets that aberrantly promote, inhibit or reverse aging. Ex situ culture of patient derived cells for identifying secreted factors in tissue regeneration and aging provides opportunities in developing therapeutic and personalized medicine strategies. Identification and validation of human secreted factors in tissue regeneration requires long-term stabile scaffold culture conditions that are different from those previously reported for cell lines used as cell models for aging. We describe a 3 dimensional (3D) platform utilizing non-biogenic and non-labile poly ε-caprolactone scaffolds that supports maintenance of long-term continuous cultures of human stem cells, in vitro generated 3D organoids and patient derived tissue. Combined with animal component free culture media, non-biogenic scaffolds are suitable for proteomic and glycobiological analyses to identify human factors in aging. Applications of electrospun nanofiber technologies in 3D cell culture allow for ex situ screening and the development of patient personalized therapeutic strategies and predicting their effectiveness in mitigating or promoting aging., (Copyright © 2024. Published by Elsevier Inc.)

Glial cells provide physical and chemical support and protection for neurons and for the extracellular compartments of neural tissue through secretion of soluble factors, insoluble scaffolds, and vesicles. Additionally, glial cells have regenerative capacity by remodeling their physical microenvironment and changing physiological properties of diverse cell types in their proximity. Various types of aberrant glial and macrophage cells are associated with human diseases, disorders, and malignancy. We previously demonstrated that transmembrane protein, TMEM230 has tissue revascularization and regenerating capacity by its ability to secrete pro-angiogenic factors and metalloproteinases, inducing endothelial cell sprouting and channel formation. In healthy normal neural tissue, TMEM230 is predominantly expressed in glial and marcophate cells, suggesting a prominent role in neural tissue homeostasis. TMEM230 regulation of the endomembrane system was supported by co-expression with RNASET2 (lysosome, mitochondria, and vesicles) and STEAP family members (Golgi complex). Intracellular trafficking and extracellular secretion of glial cellular components are associated with endocytosis, exocytosis and phagocytosis mediated by motor proteins. Trafficked components include metalloproteins, metalloproteinases, glycans, and glycoconjugate processing and digesting enzymes that function in phagosomes and vesicles to regulate normal neural tissue microenvironment, homeostasis, stress response, and repair following neural tissue injury or degeneration. Aberrantly high sustained levels TMEM230 promotes metalloprotein expression, trafficking and secretion which contribute to tumor associated infiltration and hypervascularization of high tumor grade gliomas. Following injury of the central nervous or peripheral systems, transcient regulated upregulation of TMEM230 promotes tissue wound healing, remodeling and revascularization by activating glial and macrophage generated microchannels/microtubules (referred to as vascular mimicry) and blood vessel sprouting and branching. Our results support that TMEM230 may act as a master regulator of motor protein mediated trafficking and compartmentalization of a large class of metalloproteins in gliomas and gliosis., (Copyright © 2024. Published by Elsevier Inc.)

Introduction: Single-cell (SC) gene expression analysis is crucial to dissect the complex cellular heterogeneity of solid tumors, which is one of the main obstacles for the development of effective cancer treatments. Such tumors typically contain a mixture of cells with aberrant genomic and transcriptomic profiles affecting specific sub-populations that might have a pivotal role in cancer progression, whose identification eludes bulk RNA-sequencing approaches. We present scMuffin, an R package that enables the characterization of cell identity in solid tumors on the basis of a various and complementary analyses on SC gene expression data., Results: scMuffin provides a series of functions to calculate qualitative and quantitative scores, such as: expression of marker sets for normal and tumor conditions, pathway activity, cell state trajectories, Copy Number Variations, transcriptional complexity and proliferation state. Thus, scMuffin facilitates the combination of various evidences that can be used to distinguish normal and tumoral cells, define cell identities, cluster cells in different ways, link genomic aberrations to phenotypes and identify subtle differences between cell subtypes or cell states. We analysed public SC expression datasets of human high-grade gliomas as a proof-of-concept to show the value of scMuffin and illustrate its user interface. Nevertheless, these analyses lead to interesting findings, which suggest that some chromosomal amplifications might underlie the invasive tumor phenotype and the presence of cells that possess tumor initiating cells characteristics., Conclusions: The analyses offered by scMuffin and the results achieved in the case study show that our tool helps addressing the main challenges in the bioinformatics analysis of SC expression data from solid tumors., (© 2023. The Author(s).)