RNA-Based Strategies for Cancer Therapy: In Silico Design and Evaluation of ASOs for Targeted Exon Skipping.

Precision medicine in oncology has made significant progress in recent years by approving drugs that target specific genetic mutations. However, many cancer driver genes remain challenging to pharmacologically target ("undruggable"). To tackle this issue, RNA-based methods like antisense oligonucleotides (ASOs) that induce targeted exon skipping (ES) could provide a promising alternative. In this work, a comprehensive computational procedure is presented, focused on the development of ES-based cancer treatments. The procedure aims to produce specific protein variants, including inactive oncogenes and partially restored tumor suppressors. This novel computational procedure encompasses target-exon selection, in silico prediction of ES products, and identification of the best candidate ASOs for further experimental validation. The method was effectively employed on extensively mutated cancer genes, prioritized according to their suitability for ES-based interventions. Notable genes, such as NRAS and VHL, exhibited potential for this therapeutic approach, as specific target exons were identified and optimal ASO sequences were devised to induce their skipping. To the best of our knowledge, this is the first computational procedure that encompasses all necessary steps for designing ASO sequences tailored for targeted ES, contributing with a versatile and innovative approach to addressing the challenges posed by undruggable cancer driver genes and beyond.

Mouse dendritic cells in the steady state: Hypoxia, autophagy, and stem cell factor.

Dendritic cells (DCs) are innate immune cells with a central role in immunity and tolerance. Under steady-state, DCs are scattered in tissues as resting cells. Upon infection or injury, DCs get activated and acquire the full capacity to prime antigen-specific CD4+ and CD8+ T cells, thus bridging innate and adaptive immunity. By secreting different sets of cytokines and chemokines, DCs orchestrate diverse types of immune responses, from a classical proinflammatory to an alternative pro-repair one. DCs are highly heterogeneous, and physiological differences in tissue microenvironments greatly contribute to variations in DC phenotype. Oxygen tension is normally low in some lymphoid areas, including bone marrow (BM) hematopoietic niches; nevertheless, the possible impact of tissue hypoxia on DC physiology has been poorly investigated. We assessed whether DCs are hypoxic in BM and spleen, by staining for hypoxia-inducible-factor-1α subunit (HIF-1α), the master regulator of hypoxia-induced response, and pimonidazole (PIM), a hypoxic marker, and by flow cytometric analysis. Indeed, we observed that mouse DCs have a hypoxic phenotype in spleen and BM, and showed some remarkable differences between DC subsets. Notably, DCs expressing membrane c-kit, the receptor for stem cell factor (SCF), had a higher PIM median fluorescence intensity (MFI) than c-kit- DCs, both in the spleen and in the BM. To determine whether SCF (a.k.a. kit ligand) has a role in DC hypoxia, we evaluated molecular pathways activated by SCF in c-kit+ BM-derived DCs cultured in hypoxic conditions. Gene expression microarrays and gene set enrichment analysis supported the hypothesis that SCF had an impact on hypoxia response and inhibited autophagy-related gene sets. Our results suggest that hypoxic response and autophagy, and their modulation by SCF, can play a role in DC homeostasis at the steady state, in agreement with our previous findings on SCF's role in DC survival.

Transcriptional Profiling of Three Pseudomonas syringae pv. actinidiae Biovars Reveals Different Responses to Apoplast-Like Conditions Related to Strain Virulence on the Host.

Pseudomonas syringae pv. actinidiae is a phytopathogen that causes devastating bacterial canker in kiwifruit. Among five biovars defined by genetic, biochemical, and virulence traits, P. syringae pv. actinidiae biovar 3 (Psa3) is the most aggressive and is responsible for the most recent reported outbreaks; however, the molecular basis of its heightened virulence is unclear. Therefore, we designed the first P. syringae multistrain whole-genome microarray, encompassing biovars Psa1, Psa2, and Psa3 and the well-established model P. syringae pv. tomato, and analyzed early bacterial responses to an apoplast-like minimal medium. Transcriptomic profiling revealed i) the strong activation in Psa3 of all hypersensitive reaction and pathogenicity (hrp) and hrp conserved (hrc) cluster genes, encoding components of the type III secretion system required for bacterial pathogenicity and involved in responses to environmental signals; ii) potential repression of the hrp/hrc cluster in Psa2; and iii) activation of flagellum-dependent cell motility and chemotaxis genes in Psa1. The detailed investigation of three gene families encoding upstream regulatory proteins (histidine kinases, their cognate response regulators, and proteins with diguanylate cyclase or phosphodiesterase domains) indicated that cyclic di-GMP may be a key regulator of virulence in P. syringae pv. actinidiae biovars. The gene expression data were supported by the quantification of biofilm formation. Our findings suggest that diverse early responses to the host apoplast, even among bacteria belonging to the same pathovar, can lead to different virulence strategies and may explain the differing outcomes of infections. Based on our detailed structural analysis of hrp operons, we also propose a revision of hrp cluster organization and operon regulation in P. syringae.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

A Census and Categorization Method of Epitranscriptomic Marks.

In the past few years, thorough investigation of chemical modifications operated in the cells on ribonucleic acid (RNA) molecules is gaining momentum. This new field of research has been dubbed "epitranscriptomics", in analogy to best-known epigenomics, to stress the potential of ensembles of RNA modifications to constitute a post-transcriptional regulatory layer of gene expression orchestrated by writer, reader, and eraser RNA-binding proteins (RBPs). In fact, epitranscriptomics aims at identifying and characterizing all functionally relevant changes involving both non-substitutional chemical modifications and editing events made to the transcriptome. Indeed, several types of RNA modifications that impact gene expression have been reported so far in different species of cellular RNAs, including ribosomal RNAs, transfer RNAs, small nuclear RNAs, messenger RNAs, and long non-coding RNAs. Supporting functional relevance of this largely unknown regulatory mechanism, several human diseases have been associated directly to RNA modifications or to RBPs that may play as effectors of epitranscriptomic marks. However, an exhaustive epitranscriptome's characterization, aimed to systematically classify all RNA modifications and clarify rules, actors, and outcomes of this promising regulatory code, is currently not available, mainly hampered by lack of suitable detecting technologies. This is an unfortunate limitation that, thanks to an unprecedented pace of technological advancements especially in the sequencing technology field, is likely to be overcome soon. Here, we review the current knowledge on epitranscriptomic marks and propose a categorization method based on the reference ribonucleotide and its rounds of modifications ("stages") until reaching the given modified form. We believe that this classification scheme can be useful to coherently organize the expanding number of discovered RNA modifications.

TP53 regulates miRNA association with AGO2 to remodel the miRNA-mRNA interaction network.

DNA damage activates TP53-regulated surveillance mechanisms that are crucial in suppressing tumorigenesis. TP53 orchestrates these responses directly by transcriptionally modulating genes, including microRNAs (miRNAs), and by regulating miRNA biogenesis through interacting with the DROSHA complex. However, whether the association between miRNAs and AGO2 is regulated following DNA damage is not yet known. Here, we show that, following DNA damage, TP53 interacts with AGO2 to induce or reduce AGO2's association of a subset of miRNAs, including multiple let-7 family members. Furthermore, we show that specific mutations in TP53 decrease rather than increase the association of let-7 family miRNAs, reducing their activity without preventing TP53 from interacting with AGO2. This is consistent with the oncogenic properties of these mutants. Using AGO2 RIP-seq and PAR-CLIP-seq, we show that the DNA damage-induced increase in binding of let-7 family members to the RISC complex is functional. We unambiguously determine the global miRNA-mRNA interaction networks involved in the DNA damage response, validating them through the identification of miRNA-target chimeras formed by endogenous ligation reactions. We find that the target complementary region of the let-7 seed tends to have highly fixed positions and more variable ones. Additionally, we observe that miRNAs, whose cellular abundance or differential association with AGO2 is regulated by TP53, are involved in an intricate network of regulatory feedback and feedforward circuits. TP53-mediated regulation of AGO2-miRNA interaction represents a new mechanism of miRNA regulation in carcinogenesis.

The role of TP53 in miRNA loading onto AGO2 and in remodelling the miRNA-mRNA interaction network.

BACKGROUND: DNA damage transactivates tumour protein p53 (TP53)-regulated surveillance, crucial in suppressing tumorigenesis. TP53 mediates this process directly by transcriptionally modulating gene and microRNA (miRNA) expression and indirectly by regulating miRNA biogenesis. However, the role of TP53 in regulating miRNA-AGO2 loading and global changes in AGO2 binding to its gene targets in response to DNA damage are unknown. These processes might be novel mechanisms by which TP53 regulates miRNAs in response to DNA damage. METHODS: To show the network of miRNA-mRNA interactions that occur in response to DNA damage, we stimulated TP53 wild-type and null cell-lines with doxorubicin and performed RNA sequencing from total RNA (RNA-Seq) and AGO2-immunoprecipitated RNA (AGO2-RIP-Seq). We used a combined AGO2 RIP-seq and AGO2 PAR-CLIP-seq (photoactivatable-ribonucleoside-enhanced cross-linking and immunoprecipitation) approach to determine the exact sites of interaction between the AGO2-bound miRNAs and their mRNA targets. FINDINGS: TP53 directly associated with AGO2, and induced and reduced loading of a subset of miRNAs, including the lethal 7 (let-7) miRNA family members, onto AGO2 in response to DNA damage. Although mutated TP53 maintained its capacity to interact with AGO2, it mediated unloading instead of loading of let-7 family miRNAs, thereby reducing their activity. We determined the miRNA-mRNA interaction networks involved in the response to DNA damage both in the presence and absence of TP53. Furthermore, we showed that miRNAs whose cellular abundance or differential loading onto AGO2 was regulated by TP53 were involved in an intricate network of regulatory feedback and feedforward circuits that fine-tuned gene expression levels in response to DNA damage to permit the repair of DNA damage or initiation of programmed cell death. INTERPRETATION: Control of AGO2 loading by TP53 is a new mechanism of miRNA regulation in carcinogenesis. FUNDING: UK Medical Research Council, Action Against Cancer.

Integrated molecular analysis to investigate the role of microRNAs in pancreatic tumour growth and progression.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNAs involved in the post-transcriptional regulation of mRNAs and are aberrantly expressed in cancer with important roles in tumorigenesis. A broad analysis of the combined effects of altered activities of miRNAs in pancreatic ductal adenocarcinoma (PDAC) has not been done, and how miRNAs might affect tumour progression or patient outcomes is unclear. METHODS: We combined data from miRNA and mRNA expression profiles from PDAC and normal pancreas samples (each n=9) and used bioinformatic analyses to identify a miRNA-mRNA regulatory network in PDAC. We validated our findings in PDAC cell-lines (PANC-1, MIA PaCa-2, LPc006, and LPc167), subcutaneous PDAC xenografts in mice, and laser capture microdissected PDACs from patients (n=91). We used this information to identify miRNAs that contributed most to tumorigenesis. FINDINGS: We identified three miRNAs (miR-21, miR-23a, and miR-27a) that acted as cooperative repressors of a network of tumour suppressor genes that included PDCD4, BTG2, and NEDD4L. Inhibition of miR-21, miR-23a, and miR-27a had synergistic effects in reducing proliferation of PDAC cells in culture and the growth of xenograft tumours. The level of inhibition was greater than that of silencing oncomiR-21 alone. In PDACs from patients, high levels of the combination of miR-21, miR-23a, and miR-27a was a strong independent predictor of short overall survival after surgical resection (hazard ratio 3·21, 95% CI 1·78-5·78). High expression of this combination was also associated with a more aggressive tumour phenotype: more microscopic tumour infiltration at resection margin and increased perineural invasion. INTERPRETATION: In an integrated data analysis, we identified functional miRNA-mRNA interactions that contribute to PDAC growth. These findings indicate that miRNAs act together to promote tumour progression and that future therapeutic strategies might require inhibition of several miRNAs. Furthermore, high tumour expression of the miR-21, miR-23a, and miR-27a combination could have potential use in the future as a prognostic signature for patients with PDAC. FUNDING: Peel Medical Research Trust, Alliance Family Foundation, Action Against Cancer, National Institute for Health Research, Association for International Cancer Research, Jason Boas Fellowship, Imperial Biomedical Research Centre, Rosetrees Trust, Joseph Ettedgui Charitable Foundation.

Increased chronic lymphocytic leukemia proliferation upon IgM stimulation is sustained by the upregulation of miR-132 and miR-212.

To assess the involvement of microRNAs (miRNAs) in B-cell receptor (BCR) stimulation, we first evaluated miRNA profiling following IgM cross-linking in chronic lymphocytic leukemia (CLL) cells and in normal B lymphocytes. Second, we combined miRNA and gene expression data to identify putative miRNA functional networks. miRNA profiling showed distinctive patterns of regulation after stimulation in leukemic versus normal B lymphocytes and identified a differential responsiveness to BCR engagement in CLL subgroups according to the immunoglobulin heavy chain variable region mutational status and clinical outcome. The most significantly modulated miRNAs in stimulated CLL are miR-132 and miR-212. Notably, these miRNAs appeared regulated in progressive but not in stable CLL. Accordingly, gene profiling showed a significant transcriptional response to stimulation exclusively in progressive CLL. Based on these findings, we combined miRNA and gene expression data to investigate miR-132 and miR-212 candidate interactions in this CLL subgroup. Correlation analysis pointed to a link between these miRNAs and RB/E2F and TP53 cascades with proproliferative effects, as corroborated by functional analyses. Finally, basal levels of miR-132 and miR-212 were measured in an independent cohort of 20 unstimulated CLL cases and both showed lower expression in progressive compared to stable patients, suggesting an association between the expression of these molecules and disease prognosis. Overall, our results support a model involving miR-132 and miR-212 upregulation in sustaining disease progression in CLL. These miRNAs may therefore provide new valuable strategies for therapeutic intervention.

MicroRNAs cooperatively inhibit a network of tumor suppressor genes to promote pancreatic tumor growth and progression.

BACKGROUND & AIMS: There has not been a broad analysis of the combined effects of altered activities of microRNAs (miRNAs) in pancreatic ductal adenocarcinoma (PDAC) cells, and it is unclear how these might affect tumor progression or patient outcomes. METHODS: We combined data from miRNA and messenger RNA (mRNA) expression profiles and bioinformatic analyses to identify an miRNA-mRNA regulatory network in PDAC cell lines (PANC-1 and MIA PaCa-2) and in PDAC samples from patients. We used this information to identify miRNAs that contribute most to tumorigenesis. RESULTS: We identified 3 miRNAs (MIR21, MIR23A, and MIR27A) that acted as cooperative repressors of a network of tumor suppressor genes that included PDCD4, BTG2, and NEDD4L. Inhibition of MIR21, MIR23A, and MIR27A had synergistic effects in reducing proliferation of PDAC cells in culture and growth of xenograft tumors in mice. The level of inhibition was greater than that of inhibition of MIR21 alone. In 91 PDAC samples from patients, high levels of a combination of MIR21, MIR23A, and MIR27A were associated with shorter survival times after surgical resection. CONCLUSIONS: In an integrated data analysis, we identified functional miRNA-mRNA interactions that contribute to growth of PDACs. These findings indicate that miRNAs act together to promote tumor progression; therapeutic strategies might require inhibition of several miRNAs.

Identification of linc-NeD125, a novel long non coding RNA that hosts miR-125b-1 and negatively controls proliferation of human neuroblastoma cells.

The human genome contains some thousands of long non coding RNAs (lncRNAs). Many of these transcripts are presently considered crucial regulators of gene expression and functionally implicated in developmental processes in Eukaryotes. Notably, despite a huge number of lncRNAs are expressed in the Central Nervous System (CNS), only a few of them have been characterized in terms of molecular structure, gene expression regulation and function. In the present study, we identify linc-NeD125 as a novel cytoplasmic, neuronal-induced long intergenic non coding RNA (lincRNA). Linc-NeD125 represents the host gene for miR-125b-1, a microRNA with an established role as negative regulator of human neuroblastoma cell proliferation. Here, we demonstrate that these two overlapping non coding RNAs are coordinately induced during in vitro neuronal differentiation, and that their expression is regulated by different mechanisms. While the production of miR-125b-1 relies on transcriptional regulation, linc-NeD125 is controlled at the post-transcriptional level, through modulation of its stability. We also demonstrate that linc-NeD125 functions independently of the hosted microRNA, by reducing cell proliferation and activating the antiapoptotic factor BCL-2.

Large-scale sorting of C. elegans embryos reveals the dynamics of small RNA expression.

Caenorhabditis elegans is one of the most prominent model systems for embryogenesis, but collecting many precisely staged embryos has been impractical. Thus, early C. elegans embryogenesis has not been amenable to most high-throughput genomics or biochemistry assays. To overcome this problem, we devised a method to collect staged C. elegans embryos by fluorescence-activated cell sorting (eFACS). In a proof-of-principle experiment, we found that a single eFACS run routinely yielded tens of thousands of almost perfectly staged 1-cell stage embryos. As the earliest embryonic events are driven by posttranscriptional regulation, we combined eFACS with second-generation sequencing to profile the embryonic expression of small, noncoding RNAs. We discovered complex and orchestrated changes in the expression between and within almost all classes of small RNAs, including microRNAs and 26G-RNAs, during embryogenesis.

Mining sponge phenomena in RNA expression data.

In the last few years, the interactions among competing endogenous RNAs (ceRNAs) have been recognized as a key post-transcriptional regulatory mechanism in cell differentiation, tissue development, and disease. Notably, such sponge phenomena substracting active microRNAs from their silencing targets have been recognized as having a potential oncosuppressive, or oncogenic, role in several cancer types. Hence, the ability to predict sponges from the analysis of large expression data sets (e.g. from international cancer projects) has become an important data mining task in bioinformatics. We present a technique designed to mine sponge phenomena whose presence or absence may discriminate between healthy and unhealthy populations of samples in tumoral or normal expression data sets, thus providing lists of candidates potentially relevant in the pathology. With this aim, we search for pairs of elements acting as ceRNA for a given miRNA, namely, we aim at discovering miRNA-RNA pairs involved in phenomena which are clearly present in one population and almost absent in the other one. The results on tumoral expression data, concerning five different cancer types, confirmed the effectiveness of the approach in mining interesting knowledge. Indeed, 32 out of 33 miRNAs and 22 out of 25 protein-coding genes identified as top scoring in our analysis are corroborated by having been similarly associated with cancer processes in independent studies. In fact, the subset of miRNAs selected by the sponge analysis results in a significant enrichment of annotation for the KEGG32 pathway "microRNAs in cancer" when tested with the commonly used bioinformatic resource DAVID. Moreover, often the cancer datasets where our sponge analysis identified a miRNA as top scoring match the one reported already in the pertaining literature.

Interleukin-8 in Colorectal Cancer: A Systematic Review and Meta-Analysis of Its Potential Role as a Prognostic Biomarker.

Among soluble actors that have emerged as druggable factors, the chemokine interleukin-8 (IL-8) has emerged as a possible determinant of response to immunotherapy and targeted treatment in several cancer types; however, its prognostic/predictive role in colorectal cancer (CRC) remains to be established. We: (i) conducted a systematic review of published literature on IL-8 expression in CRC; (ii) searched public transcriptomics databases; (iii) investigated IL-8 expression, by tumor and infiltrating cells, in a series of CRC samples; and (iv) carried out a meta-analysis of published literature correlating IL-8 expression and CRC prognosis. IL-8 possesses an important role as a mediator of the bidirectional crosstalk between tumor/stromal cells. Transcriptomic analysis indicated that specific IL-8 transcripts were significantly overexpressed in CRC compared to normal colon mucosa. Moreover, in our series we observed a statistically significant correlation between PTEN-loss and IL-8 expression by infiltrating mononuclear and tumor cells. In total, 12 papers met our meta-analysis inclusion criteria, demonstrating that high IL-8 levels significantly correlated with shorter overall survival and progression-free survival. Sensitivity analysis demonstrated a highly significant correlation with outcome for circulating, but not for tissue-detected, IL-8. IL-8 is overexpressed in CRC tissues and differentially produced by tumor or stromal components depending on CRC genetic background. Moreover, circulating IL-8 represents a strong prognostic factor in CRC, suggesting its use in the refining of prognostic CRC assessment and potentially the tailoring of therapeutic strategies in individual CRC patients.

AI applications in functional genomics.

We review the current applications of artificial intelligence (AI) in functional genomics. The recent explosion of AI follows the remarkable achievements made possible by "deep learning", along with a burst of "big data" that can meet its hunger. Biology is about to overthrow astronomy as the paradigmatic representative of big data producer. This has been made possible by huge advancements in the field of high throughput technologies, applied to determine how the individual components of a biological system work together to accomplish different processes. The disciplines contributing to this bulk of data are collectively known as functional genomics. They consist in studies of: i) the information contained in the DNA (genomics); ii) the modifications that DNA can reversibly undergo (epigenomics); iii) the RNA transcripts originated by a genome (transcriptomics); iv) the ensemble of chemical modifications decorating different types of RNA transcripts (epitranscriptomics); v) the products of protein-coding transcripts (proteomics); and vi) the small molecules produced from cell metabolism (metabolomics) present in an organism or system at a given time, in physiological or pathological conditions. After reviewing main applications of AI in functional genomics, we discuss important accompanying issues, including ethical, legal and economic issues and the importance of explainability.

Characterization of B- and T-lineage acute lymphoblastic leukemia by integrated analysis of MicroRNA and mRNA expression profiles.

Acute lymphoblastic leukemia (ALL) is an heterogeneous disease comprising several subentities that differ for both immunophenotypic and molecular characteristics. Over the years, the biological understanding of this neoplasm has largely increased. Gene expression profiling has allowed to identify specific signatures for the different ALL subsets and permitted the identification of pathways deregulated by a given lesion. MicroRNAs (miRNAs) are small noncoding RNAs, which play a pivotal role in several cellular functions. In this study, we investigated miRNAs expression profiles in a series of adult ALL cases by microarray analysis. Unsupervised hierarchical clustering largely recapitulated ALL subgroups. Furthermore, we identified miR-148, miR-151, and miR-424 as discriminative of T-lineage versus B-lineage ALL; ANOVA highlighted a set of six miRNAs-namely miR-425-5p, miR-191, miR-146b, miR-128, miR-629, and miR-126-that can discriminate B-lineage ALL subgroups harboring specific molecular lesions. These results were confirmed and extended by quantitative-PCR on a further cohort of cases. Finally, we used Pearson correlation analysis to combine miRNA and gene expression profiles. The distribution of correlation coefficients generated by comparing the expression of every miRNA/gene pair in our data set shows enrichment of both positively and negatively correlated pairs over background distributions obtained using randomized data. Moreover, a clear enrichment for predicted miRNA:target pairs is observed at negative correlation coefficient intervals. Signal-to-noise ratio highlighted several miRNA/gene pairs with a possible role in the disease. In fact, gene set enrichment analysis of genes composing the selected miRNA/gene pairs displays over-representation of functional categories related to cancer and cell-cycle regulation.

A genome-wide map of conserved microRNA targets in C. elegans.

BACKGROUND: Metazoan miRNAs regulate protein-coding genes by binding the 3' UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function. RESULTS: By using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3' UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans. CONCLUSIONS: At least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources.

3dLOGO: a web server for the identification, analysis and use of conserved protein substructures.

3dLOGO is a web server for the identification and analysis of conserved protein 3D substructures. Given a set of residues in a PDB (Protein Data Bank) chain, the server detects the matching substructure(s) in a set of user-provided protein structures, generates a multiple structure alignment centered on the input substructures and highlights other residues whose structural conservation becomes evident after the defined superposition. Conserved residues are proposed to the user for highlighting functional areas, deriving refined structural motifs or building sequence patterns. Residue structural conservation can be visualized through an expressly designed Java application, 3dProLogo, which is a 3D implementation of a sequence logo. The 3dLOGO server, with related documentation, is available at http://3dlogo.uniroma2.it/

[Prevalence of dementia in institutionalized patients. The RESYDEM study]. / Prevalencia de demencia en pacientes institucionalizados: estudio RESYDEM.

INTRODUCTION: To determine the prevalence of dementia in nursing homes in Spain and to analyze the associated factors in an elderly population in the institutional setting. MATERIAL AND METHODS: We performed a multicenter, cross-sectional, observational study of 852 residents of public, private and state-assisted nursing homes throughout Spain. Dementia was diagnosed according to the DSM-IV-TR clinical criteria. The Hughes Clinical Dementia Rating scale was used to measure global impairment or the global severity of dementia. Sociodemographic, clinical and neuropsychological variables, together with the pharmacological treatments prescribed to the participants, were recorded. RESULTS: The overall prevalence of dementia was 61.7% (95% CI 58.4-65.1) and that of Alzheimer's disease was 16.9% (95% CI 14.3-19.5). Vascular dementia was found in 7.3% (95% CI 5.5-9.1). Female sex was independently associated with a greater frequency of dementia. The prevalence of dementia increased with age. Only 18.8% (95% CI 15.4-22.3) of the patients diagnosed with dementia received specific treatment for the disorder. CONCLUSIONS: Two-thirds of the elderly persons living in nursing homes in Spain have dementia. Undertreatment of this disease is common. Increased awareness among health care professionals is important for the early diagnosis and appropriate management of dementia, which would represent a radical change in the approach to this disease.

Plant and fungus transcriptomic data from grapevine berries undergoing artificially-induced noble rot caused by Botrytis cinerea.

Noble rot is a latent infection of grape berries caused by the necrotrophic fungus Botrytis cinerea, which develops under specific climatic conditions. The infected berries undergo biochemical and metabolic changes, associated with a rapid withering, which altogether offer interesting organoleptic features to sweet white wines. In this paper, we provide RNAseq datasets (raw and normalized counts as well as differentially expressed genes lists) of the transcriptome profiles of both grapevine berries (Vitis vinifera cv. Garganega) and B. cinerea during the establishment of noble rot, artificially induced in controlled conditions. The sequencing data are available in the NCBI GEO database under accession number GSE116741. These data were exploited in a comprehensive meta-analysis of gene expression during noble rot infection, gray mold and post-harvest withering. This highlighted an important common transcriptional reprogramming in different botrytized grape berry varieties and led to the identification of key genes specifically modulated during noble rot infection, which are described in the article entitled "Specific molecular interactions between Vitis vinifera and Botrytis cinerea are required for noble rot development in grape berries" Lovato et al., 2019.

Inverse Problems in Systems Biology: A Critical Review.

Systems Biology may be assimilated to a symbiotic cyclic interplaying between the forward and inverse problems. Computational models need to be continuously refined through experiments and in turn they help us to make limited experimental resources more efficient. Every time one does an experiment we know that there will be some noise that can disrupt our measurements. Despite the noise certainly is a problem, the inverse problems already involve the inference of missing information, even if the data is entirely reliable. So the addition of a certain limited noise does not fundamentally change the situation but can be used to solve the so-called ill-posed problem, as defined by Hadamard. It can be seen as an extra source of information. Recent studies have shown that complex systems, among others the systems biology, are poorly constrained and ill-conditioned because it is difficult to use experimental data to fully estimate their parameters. For these reasons was born the concept of sloppy models, a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. Furthermore the concept of sloppy models contains also the concept of un-identifiability, because the models are characterized by many parameters that are poorly constrained by experimental data. Then a strategy needs to be designed to infer, analyze, and understand biological systems. The aim of this work is to provide a critical review to the inverse problems in systems biology defining a strategy to determine the minimal set of information needed to overcome the problems arising from dynamic biological models that generally may have many unknown, non-measurable parameters.