Non-interventional, 5-year retrospective data of home parenteral nutrition in patients with benign chronic intestinal failure: Analysis of an Italian nurse registry (SERECARE II).

OBJECTIVE: This study is an assessment of home parenteral nutrition service performance and safety and efficacy outcomes in patients with benign chronic intestinal failure. METHODS: This is a retrospective, non-interventional, and multicenter study. Data were collected by trained nurses and recorded in a dedicated registry (SERECARE). RESULTS: From January 1, 2013 to June 30, 2018, data from a total of 683 patients with benign chronic intestinal failure were entered in the registry. Patients included 208 pediatric (53.8% male; median age = 4.0 y) and 475 adult (47.6% male; median age = 59.0 y) participants. On average, patients were visited 5.4 ± 4.5 times and received 1.4 ± 0.8 training sessions. Retraining was not common and mostly due to change of therapy or change of caregiver. Of 939 complications, 40.9% were related to the central venous catheter and were mostly infectious (n = 182) and mechanical (n = 187). The rate of infectious and mechanical complications per 1000 catheter days decreased over 5 y (0.30-0.15 and 0.33 -0.19, respectively). The rate of complications per 1000 catheter days and the mean complications per patient were higher in pediatric than in adult patients. The hospitalization rate was 1.01 per patient throughout the study period. These data were similar to those registered in a previous study period (2002-2011) (n = 1.53 per patient). Changes over time in the efficacy variables were mostly small and non-significant. CONCLUSIONS: This study confirms the importance of setting up and maintaining structured registries to monitor and improve home parenteral nutrition care. Safety outcomes have improved over the years, most likely due to the underlying efficient nursing service.

Overview of data preprocessing for machine learning applications in human microbiome research.

Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical specificities of the data (e.g., sparse, over-dispersed, compositional, inter-variable dependency). This mini review explores preprocessing and transformation methods applied in recent human microbiome studies to address microbiome data analysis challenges. Our results indicate a limited adoption of transformation methods targeting the statistical characteristics of microbiome sequencing data. Instead, there is a prevalent usage of relative and normalization-based transformations that do not specifically account for the specific attributes of microbiome data. The information on preprocessing and transformations applied to the data before analysis was incomplete or missing in many publications, leading to reproducibility concerns, comparability issues, and questionable results. We hope this mini review will provide researchers and newcomers to the field of human microbiome research with an up-to-date point of reference for various data transformation tools and assist them in choosing the most suitable transformation method based on their research questions, objectives, and data characteristics.

Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action.

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.

Whole-Exome and Transcriptome Sequencing Expands the Genotype of Majewski Osteodysplastic Primordial Dwarfism Type II.

Microcephalic Osteodysplastic Primordial Dwarfism type II (MOPDII) represents the most common form of primordial dwarfism. MOPD clinical features include severe prenatal and postnatal growth retardation, postnatal severe microcephaly, hypotonia, and an increased risk for cerebrovascular disease and insulin resistance. Autosomal recessive biallelic loss-of-function genomic variants in the centrosomal pericentrin (PCNT) gene on chromosome 21q22 cause MOPDII. Over the past decade, exome sequencing (ES) and massive RNA sequencing have been effectively employed for both the discovery of novel disease genes and to expand the genotypes of well-known diseases. In this paper we report the results both the RNA sequencing and ES of three patients affected by MOPDII with the aim of exploring whether differentially expressed genes and previously uncharacterized gene variants, in addition to PCNT pathogenic variants, could be associated with the complex phenotype of this disease. We discovered a downregulation of key factors involved in growth, such as IGF1R, IGF2R, and RAF1, in all three investigated patients. Moreover, ES identified a shortlist of genes associated with deleterious, rare variants in MOPDII patients. Our results suggest that Next Generation Sequencing (NGS) technologies can be successfully applied for the molecular characterization of the complex genotypic background of MOPDII.

Ten simple rules on how to develop a stakeholder engagement plan.

To make research responsible and research outcomes meaningful, it is necessary to communicate our research and to involve as many relevant stakeholders as possible, especially in application-oriented-including information and communications technology (ICT)-research. Nowadays, stakeholder engagement is of fundamental importance to project success and achieving the expected impact and is often mandatory in a third-party funding context. Ultimately, research and development can only be successful if people react positively to the results and benefits generated by a project. For the wider acceptance of research outcomes, it is therefore essential that the public is made aware of and has an opportunity to discuss the results of research undertaken through two-way communication (interpersonal communication) with researchers. Responsible Research and Innovation (RRI), an approach that anticipates and assesses potential implications and societal expectations regarding research and innovation, aims to foster inclusive and sustainable research and innovation. Research and innovation processes need to become more responsive and adaptive to these grand challenges. This implies, among other things, the introduction of broader foresight and impact assessments for new technologies beyond their anticipated market benefits and risks. Therefore, this article provides a structured workflow that explains "how to develop a stakeholder engagement plan" step by step.

Participation of nurses and allied health professionals in research activities: a survey in an academic tertiary pediatric hospital.

BACKGROUND: Involvement in research activities is complex in pediatric nursing and allied health professionals (AHPs). It is important to understand which individual factors are associated with it to inform policy makers in promoting research. METHODS: A cross-sectional observational study was conducted to describe the level of participation in research activities over the last ten years of nurses and AHPs working in a tertiary pediatric hospital. A large sample of nurses and AHPs working in an Italian academic tertiary pediatric hospital completed an online self-report questionnaire between June and December 2018. Three multivariate logistic regression analyses were performed to predict participation in research projects, speaking at conferences, and writing scientific articles. RESULTS: Overall, data from 921 health professionals were analyzed (response rate = 66%), of which about 21% (n = 196) reported participating in a research project, while 33% (n = 297) had attended a scientific conference as a speaker, and 11% (n = 94) had written at least one scientific paper. Having a Master or a Regional Advanced Course, working as an AHP or a ward manager, as well as regularly reading scientific journals and participation in an internal hospital research group or attendance in a specific course about research in the hospital, significantly predicted participation in research projects, speaking at conferences and writing scientific papers. It is important to foster research interest and competencies among health professionals to improve participation in research projects, speaking at conferences, and writing scientific papers. CONCLUSIONS: Overall, we found a good level of attendance at conferences as speakers (33%), a moderate level of participation in research (21%), and low levels for writing scientific papers (11%). Our study highlighted the need to support participation in research activities among nurses and AHPs. Policymakers should identify strategies to promote research among nurses and AHPs, such as protected rewarded time for research, specific education, strengthened collaboration with academics, and financial support. Moreover, hospital managers should promote the development of research culture among health professionals, to improve their research competencies and evidence-based practice.

Real food in enteral nutrition for chronically ill children: overview and practical clinical cases.

BACKGROUND: Many feeding strategies may be used in chronically ill children on enteral nutrition. Interest is currently growing in real food-based enteral nutrition. A new tube feeding formula with real food ingredients is currently commercially available in Europe. CASE REPORTS: By focusing on four clinical cases, this article illustrates the use of a tube feeding formula with real food ingredients in pediatric patients with various complex conditions. The formula contains a milk-based mixture of peas, green beans, peaches, carrots, and chicken, and provides 1.2 kcal/ml. It was offered under medical supervision and after full consideration of all feeding options. CONCLUSIONS: Formula choice appears to be based on clinical experience and must be individualized to patients' characteristics and needs. Real food-containing formulas seem to improve tolerance and feeding outcomes as well as promote family inclusion and mealtime engagement, but further studies are warranted.

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.

The Ketogenic Diet Increases In Vivo Glutathione Levels in Patients with Epilepsy.

The Ketogenic Diet (KD) is a high-fat, low-carbohydrate diet that has been utilized as the first line treatment for contrasting intractable epilepsy. It is responsible for the presence of ketone bodies in blood, whose neuroprotective effect has been widely shown in recent years but remains unclear. Since glutathione (GSH) is implicated in oxidation-reduction reactions, our aim was to monitor the effects of KD on GSH brain levels by means of magnetic resonance spectroscopy (MRS). MRS was acquired from 16 KD patients and seven age-matched Healthy Controls (HC). We estimated metabolite concentrations with linear combination model (LCModel), assessing differences between KD and HC with t-test. Pearson was used to investigate GHS correlations with blood serum 3-B-Hydroxybutyrate (3HB) concentrations and with number of weekly epileptic seizures. The results have shown higher levels of brain GSH for KD patients (2.5 ± 0.5 mM) compared to HC (2.0 ± 0.5 mM). Both blood serum 3HB and number of seizures did not correlate with GSH concentration. The present study showed a significant increase in GSH in the brain of epileptic children treated with KD, reproducing for the first time in humans what was previously observed in animal studies. Our results may suggest a pivotal role of GSH in the antioxidant neuroprotective effect of KD in the human brain.

Plant miRNAs Reduce Cancer Cell Proliferation by Targeting MALAT1 and NEAT1: A Beneficial Cross-Kingdom Interaction.

MicroRNAs (miRNAs) are ubiquitous regulators of gene expression, evolutionarily conserved in plants and mammals. In recent years, although a growing number of papers debate the role of plant miRNAs on human gene expression, the molecular mechanisms through which this effect is achieved are still not completely elucidated. Some evidence suggest that this interaction might be sequence specific, and in this work, we investigated this possibility by transcriptomic and bioinformatics approaches. Plant and human miRNA sequences from primary databases were collected and compared for their similarities (global or local alignments). Out of 2,588 human miRNAs, 1,606 showed a perfect match of their seed sequence with the 5' end of 3,172 plant miRNAs. Further selections were applied based on the role of the human target genes or of the miRNA in cell cycle regulation (as an oncogene, tumor suppressor, or a biomarker for prognosis, or diagnosis in cancer). Based on these criteria, 20 human miRNAs were selected as potential functional analogous of 7 plant miRNAs, which were in turn transfected in different cell lines to evaluate their effect on cell proliferation. A significant decrease was observed in colorectal carcinoma HCT116 cell line. RNA-Seq demonstrated that 446 genes were differentially expressed 72 h after transfection. Noteworthy, we demonstrated that the plant mtr-miR-5754 and gma-miR4995 directly target the tumor-associated long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and nuclear paraspeckle assembly transcript 1 (NEAT1) in a sequence-specific manner. In conclusion, according to other recent discoveries, our study strengthens and expands the hypothesis that plant miRNAs can have a regulatory effect in mammals by targeting both protein-coding and non-coding RNA, thus suggesting new biotechnological applications.

Ten simple rules on how to write a standard operating procedure.

Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.

Microarray data and pathway analyses of peripheral blood mononuclear cells from healthy subjects after a three weeks grape-rich diet.

Using Human Gene Expression Microarrays (Agilent) technologies, we investigated changes of the level of gene expression in peripheral blood mononuclear cells of healthy subjects after 21 days of fresh table grape-rich diet and after an additional 28-day washout. Several hundreds of genes were differentially expressed after grape intake or after washout. The functional analysis of these genes detected significant changes in key processes such as inflammation and immunity, thrombosis, DNA and protein repair, autophagy and mitochondrial biogenesis. Moreover, fresh grape intake was found to influence the expression of many long non-coding RNA genes. The data can be valuable for researchers interested in nutrigenetics and nutrigenomics studies and are related to the research article "Gene expression signature induced by grape intake in healthy subjects reveals wide-spread beneficial effects on PBMCs" [1].

Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering.

BACKGROUND: The study of functional associations between ncRNAs and human diseases is a pivotal task of modern research to develop new and more effective therapeutic approaches. Nevertheless, it is not a trivial task since it involves entities of different types, such as microRNAs, lncRNAs or target genes whose expression also depends on endogenous or exogenous factors. Such a complexity can be faced by representing the involved biological entities and their relationships as a network and by exploiting network-based computational approaches able to identify new associations. However, existing methods are limited to homogeneous networks (i.e., consisting of only one type of objects and relationships) or can exploit only a small subset of the features of biological entities, such as the presence of a particular binding domain, enzymatic properties or their involvement in specific diseases. RESULTS: To overcome the limitations of existing approaches, we propose the system LP-HCLUS, which exploits a multi-type hierarchical clustering method to predict possibly unknown ncRNA-disease relationships. In particular, LP-HCLUS analyzes heterogeneous networks consisting of several types of objects and relationships, each possibly described by a set of features, and extracts multi-type clusters that are subsequently exploited to predict new ncRNA-disease associations. The extracted clusters are overlapping, hierarchically organized, involve entities of different types, and allow LP-HCLUS to catch multiple roles of ncRNAs in diseases at different levels of granularity. Our experimental evaluation, performed on heterogeneous attributed networks consisting of microRNAs, lncRNAs, diseases, genes and their known relationships, shows that LP-HCLUS is able to obtain better results with respect to existing approaches. The biological relevance of the obtained results was evaluated according to both quantitative (i.e., TPR@k, Areas Under the TPR@k, ROC and Precision-Recall curves) and qualitative (i.e., according to the consultation of the existing literature) criteria. CONCLUSIONS: The obtained results prove the utility of LP-HCLUS to conduct robust predictive studies on the biological role of ncRNAs in human diseases. The produced predictions can therefore be reliably considered as new, previously unknown, relationships among ncRNAs and diseases.

The need for standardisation in life science research - an approach to excellence and trust.

Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However  for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation.

Exploiting transfer learning for the reconstruction of the human gene regulatory network.

MOTIVATION: The reconstruction of gene regulatory networks (GRNs) from gene expression data has received increasing attention in recent years, due to its usefulness in the understanding of regulatory mechanisms involved in human diseases. Most of the existing methods reconstruct the network through machine learning approaches, by analyzing known examples of interactions. However, (i) they often produce poor results when the amount of labeled examples is limited, or when no negative example is available and (ii) they are not able to exploit information extracted from GRNs of other (better studied) related organisms, when this information is available. RESULTS: In this paper, we propose a novel machine learning method that overcomes these limitations, by exploiting the knowledge about the GRN of a source organism for the reconstruction of the GRN of the target organism, by means of a novel transfer learning technique. Moreover, the proposed method is natively able to work in the positive-unlabeled setting, where no negative example is available, by fruitfully exploiting a (possibly large) set of unlabeled examples. In our experiments, we reconstructed the human GRN, by exploiting the knowledge of the GRN of Mus musculus. Results showed that the proposed method outperforms state-of-the-art approaches and identifies previously unknown functional relationships among the analyzed genes. AVAILABILITY AND IMPLEMENTATION: http://www.di.uniba.it/∼mignone/systems/biosfer/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Non-interventional, retrospective data of long-term home parenteral nutrition in patients with benign diseases: Analysis of a nurse register (SERECARE).

OBJECTIVES: The aim of this study was to evaluate the safety and efficacy of home parenteral nutrition (HPN) service in patients with benign chronic intestinal failure (CIF). METHODS: This was a 10-y retrospective, non-interventional, multicenter study conducted with adult and pediatric patients with CIF who received HPN service. We analyzed data prospectively collected from a dedicated register by HPN nurses. RESULTS: From January 2002 to December 2011 a total of 794 patients (49.7% male, median age 1 y for children and 57 y for adults) were included in the analysis. Over the 10-y period, 723 central venous catheter (CVC) complications occurred, of which 394 were infectious (54.5%), 297 were mechanical (41.1%), and 32 (3.3%) were defined as CVC-related thrombosis. The complication rate was higher in children (1.11 per patient) than in adults (0.70 per patient). During the observation period, the rates of both infectious and mechanical complications showed a global declining trend and ∼75% of patients had neither infectious nor mechanical CVC complications. HPN efficacy was evaluated in 301 patients with a minimum follow-up of 36 mo. Body mass index and Karnofsky score showed that the median growth significantly increased (P < 0.001) over baseline for adults and pediatric patients in the 0 to 2 age range. CONCLUSIONS: The use of a structured register has proved to be a key strategy for monitoring the outcomes of long-term treatment, improving time efficiency, and preventing potential malpractice. To our knowledge, this is the largest survey ever documented; the results were consistent despite the heterogeneity of the centers because of duly applied standard rules and protocols.

NOTCH3 and CADASIL syndrome: a genetic and structural overview.

CADASIL syndrome is a rare disease that belongs to a group of disorders called leukodystrophies. It is well established that NOTCH3 gene on chromosome 19 is primarily responsible for the development of the CADASIL syndrome. Herein, an attempt is made to shed light on the actual molecular mechanism underlying CADASIL syndrome, through insights extracted from comprehensive evolutionary studies and in silico modelling on Notch 3 protein. In particular, we suggest the use of optical coherence tomography angiography for the detection of early signs of small vessel diseases, which are the major precursors to a repertoire of neurodegenerative conditions, including CADASIL.

Arena-Idb: a platform to build human non-coding RNA interaction networks.

BACKGROUND: High throughput technologies have provided the scientific community an unprecedented opportunity for large-scale analysis of genomes. Non-coding RNAs (ncRNAs), for a long time believed to be non-functional, are emerging as one of the most important and large family of gene regulators and key elements for genome maintenance. Functional studies have been able to assign to ncRNAs a wide spectrum of functions in primary biological processes, and for this reason they are assuming a growing importance as a potential new family of cancer therapeutic targets. Nevertheless, the number of functionally characterized ncRNAs is still too poor if compared to the number of new discovered ncRNAs. Thus platforms able to merge information from available resources addressing data integration issues are necessary and still insufficient to elucidate ncRNAs biological roles. RESULTS: In this paper, we describe a platform called Arena-Idb for the retrieval of comprehensive and non-redundant annotated ncRNAs interactions. Arena-Idb provides a framework for network reconstruction of ncRNA heterogeneous interactions (i.e., with other type of molecules) and relationships with human diseases which guide the integration of data, extracted from different sources, via mapping of entities and minimization of ambiguity. CONCLUSIONS: Arena-Idb provides a schema and a visualization system to integrate ncRNA interactions that assists in discovering ncRNA functions through the extraction of heterogeneous interaction networks. The Arena-Idb is available at http://arenaidb.ba.itb.cnr.it.

Pediatric Short Bowel Syndrome: Predicting Four-Year Outcome after Massive Neonatal Resection.

OBJECTIVES: The aim of this study was to ascertain predictors of survival, liver disease (LD), and enteral autonomy 48 months after resection in neonatal short bowel syndrome (SBS) patients with residual small bowel length (SBL) ≤40 cm. PATIENTS AND METHODS: Medical records of all SBS patients followed up between 1996 and 2016 were retrospectively reviewed. Survival rate, prevalence of LD, and of enteral autonomy were evaluated. RESULTS: Forty-seven patients were included, and 43 were still alive at the end of the study period, with cumulative 48-month survival of 91.5%. Twenty-one (45%) patients developed LD, all within the first 6 months. On the final follow-up visit, three (6%) patients were still jaundiced and progressed toward end-stage LD. LD prevalence was higher in patients with recurrent bloodstream infections (odds ratio [OR] 5.4, 95% confidence interval [CI] 1.5-19.3). Of the 43 surviving patients, 22 (51%) had enteral autonomy 48 months after resection. The probability of weaning off parenteral nutrition (PN) was strongly correlated with the remaining SBL. CONCLUSION: Survival of patients who have undergone neonatal massive small bowel resection has improved in recent years. Multidisciplinary strategies can improve the course of LD, but not the probability of weaning off PN, which seems to be strongly dependent on the anatomical profile of residual bowel. Therefore, the primary surgical approach should be as conservative as possible to gain even small amounts of intestinal length, which may be crucial in promoting intestinal adaptation.

Pediatric Chronic Intestinal Failure in Italy: Report from the 2016 Survey on Behalf of Italian Society for Gastroenterology, Hepatology and Nutrition (SIGENP).

BACKGROUND: Intestinal failure (IF) is the reduction in functioning gut mass below the minimal level necessary for adequate digestion and absorption of nutrients and fluids for weight maintenance in adults or for growth in children. There is a paucity of epidemiologic data on pediatric IF. The purpose of this study was to determine the prevalence, incidence, regional distribution and underlying diagnosis of pediatric chronic IF (CIF) requiring home parenteral nutrition (HPN) in Italy. METHODS: Local investigators were selected in 19 Italian centers either of reference for pediatric HPN or having pediatric gastroenterologists or surgeons on staff and already collaborating with the Italian Society for Pediatric Gastroenterology, Hepatology and Nutrition with regard to IF. Data requested in this survey for children at home on Parenteral Nutrition (PN) on 1 December 2016 included patient initials, year of birth, gender, family's place of residence and underlying diagnosis determining IF. RESULTS: We recorded 145 CIF patients on HPN aged ≤19 years. The overall prevalence was 14.12/million inhabitants (95% CI: 9.20-18.93); the overall incidence was 1.41/million inhabitant years (95% CI: 0.53-2.20). CONCLUSION: Our survey provides new epidemiological data on pediatric CIF in Italy; these data may be quantitatively useful in developing IF care strategy plans in all developed countries.