Review of Patient Gene Profiles Obtained through a Non-Negative Matrix Factorization-Based Framework to Determine the Role Inflammation Plays in Neuroblastoma Pathogenesis.

Neuroblastoma is the most common extracranial solid tumor in children. It is a highly heterogeneous tumor consisting of different subcellular types and genetic abnormalities. Literature data confirm the biological and clinical complexity of this cancer, which requires a wider availability of gene targets for the implementation of personalized therapy. This paper presents a study of neuroblastoma samples from primary tumors of untreated patients. The focus of this analysis is to evaluate the impact that the inflammatory process may have on the pathogenesis of neuroblastoma. Eighty-eight gene profiles were selected and analyzed using a non-negative matrix factorization framework to extract a subset of genes relevant to the identification of an inflammatory phenotype, whose targets (PIK3CG, NFATC2, PIK3R2, VAV1, RAC2, COL6A2, COL6A3, COL12A1, COL14A1, ITGAL, ITGB7, FOS, PTGS2, PTPRC, ITPR3) allow further investigation. Based on the genetic signals automatically derived from the data used, neuroblastoma could be classified according to stage rather than as a "cold" or "poorly immunogenic" tumor.

Effect of music therapy intervention on anxiety and pain during percutaneous renal biopsy: a randomized controlled trial.

Background: Percutaneous renal biopsy (PRB) may subject patients to emotional distress and pain before and during the biopsy. The aim of this study was to evaluate the effects of complementary/non-pharmacological interventions such as music therapy (MT) on anxiety, pain and satisfaction in renal patients undergoing PRB. Methods: A prospective, single-centre, single-blind, randomized controlled two-arm trial was conducted. Patients ≥18 years of age, hospitalized at the Nephrology, Dialysis and Transplantation Unit (Bari, Italy) and scheduled for PRB were screened. Participants were assigned to standard treatment (CG) or to the music therapy (MT) intervention group. Participants in the MT group received standard care and an MT intervention by a certified music therapist qualified in guided imagery and music. The CG patients received the standard of care. MT and CG patients were subjected to identical measurements (pre/post) of the parameters in the State Trait Anxiety Inventory Y1 (STAI-Y1), visual analogue scale for pain (VAS-P) and satisfaction (VAS-S) and heart rate variability. Results: A statistically significant difference in the anxiety scores after PRB between MT and CG patients (STAI-Y1 35.4 ± 6.2 versus 42.9 ± 9.0) was observed. MT also had strong and significant effects on VAS-P compared with CG (5.0 ± 1.4 versus 6.3 ± 1.3, respectively; P < .001) and VAS-S (7.8 ± 1.0 versus 6.0 ± 0.9, respectively; P < .001). Decreased activity of the sympathetic nervous system and increased activity of the parasympathetic nervous system was observed after PRB in the MT group. Conclusion: Our study supports the use of MT to mitigate the psychological anxiety, pain and sympathetic activation associated with PRB.

Cluster of resistance-inducing genes in MCF-7 cells by estrogen, insulin, methotrexate and tamoxifen extracted via NMF.

Breast cancer has become a leading cause of death for women as the economy has grown and the number of women in the labor force has increased. Several biomarkers with diagnostic, prognostic, and therapeutic implications for breast cancer have been identified in studies, leading to therapeutic advances. Resistance, on the other hand, is one of clinical practice's limitations. In this paper, we use Nonnegative Matrix Factorization to automatically extract two gene signatures from gene expression profiles of wild-type and resistance MCF-7 cells, which were then investigated further using pathways analysis and proved useful in relating resistance pathways to breast cancer regardless of the stimulus that caused it. A few extracted genes (including MAOA, IL4I1, RRM2, DUT, NME4, and SUMO3) represent new elements in the functional network for resistance in MCF-7 ER+ breast cancer. As a result of this research, a better understanding of how resistance occurs or the pathways that contribute to it may allow more effective therapies to be developed.

Role of lipidomics in assessing the functional lipid composition in breast milk.

Breast milk is the ideal source of nutrients for infants in early life. Lipids represent 2-5% of the total breast milk composition and are a major energy source providing 50% of an infant's energy intake. Functional lipids are an emerging class of lipids in breast milk mediating several different biological functions, health, and developmental outcome. Lipidomics is an emerging field that studies the structure and function of lipidome. It provides the ability to identify new signaling molecules, mechanisms underlying physiological activities, and possible biomarkers for early diagnosis and prognosis of diseases, thus laying the foundation for individualized, targeted, and precise nutritional management strategies. This emerging technique can be useful to study the major role of functional lipids in breast milk in several dimensions. Functional lipids are consumed with daily food intake; however, they have physiological benefits reported to reduce the risk of disease. Functional lipids are a new area of interest in lipidomics, but very little is known of the functional lipidome in human breast milk. In this review, we focus on the role of lipidomics in assessing functional lipid composition in breast milk and how lipid bioinformatics, a newly emerging branch in this field, can help to determine the mechanisms by which breast milk affects newborn health.

NR1H3 (LXRα) is associated with pro-inflammatory macrophages, predicts survival and suggests potential therapeutic rationales in diffuse large b-cell lymphoma.

The role of macrophages (Mo) and their prognostic impact in diffuse large B-cell lymphomas (DLBCL) remain controversial. By regulating the lipid metabolism, Liver-X-Receptors (LXRs) control Mo polarization/inflammatory response, and their pharmacological modulation is under clinical investigation to treat human cancers, including lymphomas. Herein, we surveyed the role of LXRs in DLBCL for prognostic purposes. Comparing bulk tumors with purified malignant and normal B-cells, we found an intriguing association of NR1H3, encoding for the LXR-α isoform, with the tumor microenvironment (TME). CIBERSORTx-based purification on large DLBCL datasets revealed a high expression of the receptor transcript in M1-like pro-inflammatory Mo. By determining an expression cut-off of NR1H3, we used digital measurement to validate its prognostic capacity on two large independent on-trial and real-world cohorts. Independently of classical prognosticators, NR1H3high patients displayed longer survival compared with NR1H3low cases and a high-resolution Mo GEP dissection suggested a remarkable transcriptional divergence between subgroups. Overall, our findings indicate NR1H3 as a Mo-related biomarker identifying patients at higher risk and prompt future preclinical studies investigating its mouldability for therapeutic purposes.

Colorectal cancer in Crohn's disease evaluated with genes belonging to fibroblasts of the intestinal mucosa selected by NMF.

Crohn's disease (CD) is a type of chronic, inflammatory bowel disease (IBD) which affects any part of the gastrointestinal tract. This study aims to understand the mechanism which activate mucosal fibroblasts in the microenvironment of the colon in CD and colorectal carcinomas and to extract fibroblasts phenotypes via a novel framework based on non-negative factorization of matrix (NMF). The results identify a fibroblast phenotype characterized by intense pro-inflammatory activity ensured by the presence of genes belonging to the APOBEC1 family, such as APOBEC3F and APOBEC3G. These results demonstrated that there is a difference in fibroblast response in producing a pro-tumorigenic effect in CD. The different activation mechanisms could represent useful biomarkers in controlling CD development without generalizing its significance as IBD.

Electronic case report forms generation from pathology reports by ARGO, automatic record generator for onco-hematology.

The unstructured nature of Real-World (RW) data from onco-hematological patients and the scarce accessibility to integrated systems restrain the use of RW information for research purposes. Natural Language Processing (NLP) might help in transposing unstructured reports into standardized electronic health records. We exploited NLP to develop an automated tool, named ARGO (Automatic Record Generator for Onco-hematology) to recognize information from pathology reports and populate electronic case report forms (eCRFs) pre-implemented by REDCap. ARGO was applied to hemo-lymphopathology reports of diffuse large B-cell, follicular, and mantle cell lymphomas, and assessed for accuracy (A), precision (P), recall (R) and F1-score (F) on internal (n = 239) and external (n = 93) report series. 326 (98.2%) reports were converted into corresponding eCRFs. Overall, ARGO showed high performance in capturing (1) identification report number (all metrics > 90%), (2) biopsy date (all metrics > 90% in both series), (3) specimen type (86.6% and 91.4% of A, 98.5% and 100.0% of P, 92.5% and 95.5% of F, and 87.2% and 91.4% of R for internal and external series, respectively), (4) diagnosis (100% of P with A, R and F of 90% in both series). We developed and validated a generalizable tool that generates structured eCRFs from real-life pathology reports.

Analysis of fibroblast genes selected by NMF to reveal the potential crosstalk between ulcerative colitis and colorectal cancer.

Patients with ulcerative colitis (UC) have an increased risk of developing colorectal cancer (CRC). The CRC risk extent raises with increasing age, duration of symptoms, severity of inflammation and dysplasia. CRC is a complex multi-stage process and associated with UC represents 2% of all colon cancers. With the aim of clarifying some aspects of the evolution of UC towards CRC, we characterized the phenotype of fibroblasts present in the mucosa of subjects affected by UC to verify whether they can contribute to the genesis of a microenvironment favorable to tumor transformation. The fibroblast phenotype was obtained with the help of transcriptome analysis adopting a novel framework based on Nonnegative Matrix Factorization (NMF) which automatically extracts a limited number of genes from fibroblast gene expression profiles of patients with UC and CRC. These genes may be considered possible candidates in generating a permissive microenvironment for the evolution of disease under study.

Eye Vergence Responses During an Attention Task in Adults With ADHD and Clinical Controls.

Objective: ADHD patients show poor oculomotor control and recent studies show that attention-related eye vergence is weak in ADHD children. We aimed to assess vergence as a potential diagnostic biomarker for ADHD in adults. Method: We assessed the modulation in the angle of vergence while performing an attention task (N = 144), comparing the results for adults previously diagnosed with ADHD (N = 108) with age-matched clinical controls (N = 36). Results: Significant differences in eye vergence response modulation between clinical controls and ADHD patients were documented. Diagnostic test accuracy was 79%. Conclusion: In combination with an attention task, eye vergence responses could be used as an objective marker to support the clinical diagnosis of adult ADHD.

An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations.

The rapid development of high-performance technologies has greatly promoted studies of molecular oncology producing large amounts of data. Even if these data are publicly available, they need to be processed and studied to extract information useful to better understand mechanisms of pathogenesis of complex diseases, such as tumors. In this article, we illustrated a procedure for mining biologically meaningful biomarkers from microarray datasets of different tumor histotypes. The proposed methodology allows to automatically identify a subset of potentially informative genes from microarray data matrices, which differs either in the number of rows (genes) and of columns (patients). The methodology integrates nonnegative matrix factorization method, a functional enrichment analysis web tool with a properly designed gene extraction procedure to allow the analysis of omics input data with different row size. The proposed methodology has been used to mine microarray of solid tumors of different embryonic origin to verify the presence of common genes characterizing the heterogeneity of cancer-associated fibroblasts. These automatically extracted biomarkers could be used to suggest appropriate therapies to inactivate the state of active fibroblasts, thus avoiding their action on tumor progression.

Orthogonal joint sparse NMF for microarray data analysis.

The 3D microarrays, generally known as gene-sample-time microarrays, couple the information on different time points collected by 2D microarrays that measure gene expression levels among different samples. Their analysis is useful in several biomedical applications, like monitoring dose or drug treatment responses of patients over time in pharmacogenomics studies. Many statistical and data analysis tools have been used to extract useful information. In particular, nonnegative matrix factorization (NMF), with its natural nonnegativity constraints, has demonstrated its ability to extract from 2D microarrays relevant information on specific genes involved in the particular biological process. In this paper, we propose a new NMF model, namely Orthogonal Joint Sparse NMF, to extract relevant information from 3D microarrays containing the time evolution of a 2D microarray, by adding additional constraints to enforce important biological proprieties useful for further biological analysis. We develop multiplicative updates rules that decrease the objective function monotonically, and compare our approach to state-of-the-art NMF algorithms on both synthetic and real data sets.

Eye vergence responses to novel and familiar stimuli in young children.

Eye vergence is the slow movement of both eyes in opposite directions enabling binocular vision. Recently, it was suggested that vergence could be involved in orienting visual attention and memory having a role in cognitive processing of sensory information. In the present study, we assessed whether such vergence responses are observed in early childhood. We measured eye vergence responses in 43 children (12-37 months of age) while looking at novel and repeated object images. Based on previous research, we hypothesized that visual attention and Visual Short-Term Memory (VSMT) would be evidenced by differential vergence responses for both experimental conditions, i.e. repeated (familiar) vs. novel items. The results show that attention related vergence is present in early childhood and that responses to repeated images differ from the ones to novel items. Our current findings suggest that vergence mechanisms could be linking visual attention with short-term memory recognition.

Clinical Validation of Eye Vergence as an Objective Marker for Diagnosis of ADHD in Children.

OBJECTIVE: ADHD youth show poor oculomotor control. Recent research shows that attention-related eye vergence is weak in ADHD children. METHOD: To validate vergence as a marker to classify ADHD, we assessed the modulation in the angle of vergence of children ( n = 43) previously diagnosed with ADHD while performing an attention task and compared the results with age-matched clinical controls ( n = 19) and healthy peers ( n = 30). RESULTS: We observed strong vergence responses in healthy participants and weak vergence in the clinical controls. ADHD children showed no significant vergence responses. Machine-learning models classified ADHD patients ( n = 21) from healthy controls ( n = 21) with an accuracy of 96.3% (false positive [FP]: 5.12%; false negative [FN]: 0%; area under the curve [AUC]: 0.99) and ADHD children ( n = 11) from clinical controls ( n = 14) with an accuracy of 85.7% (FP: 4.5%; FN: 19.2%, AUC: 0.90). CONCLUSION: In combination with an attention task, vergence responses can be used as an objective marker to detect ADHD in children.

Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles.

BACKGROUND: Multiple myeloma (MM) is a cancer of terminally differentiated plasma that is part of a spectrum of blood diseases. The role of the micro-environment is crucial for MM clonal evolution. METHODS: This paper describes the analysis carried out on a limited number of genes automatically extracted by a nonnegative matrix factorization (NMF) based approach from gene expression profiles of bone marrow fibroblasts of patients with monoclonal gammopathy of undetermined significance (MGUS) and MM. RESULTS: Automatic exploration through NMF, combined with a motivated post-processing procedure and a pathways analysis of extracted genes, allowed to infer that a functional switch is required to lead fibroblasts to acquire pro-tumorigenic activity in the progression of the disease from MGUS to MM. CONCLUSION: The extracted biologically relevant genes may be representative of the considered clinical conditions and may contribute to a deeper understanding of tumor behavior.

Vergence responses to face stimuli in young children.

In line with a possible role of vergence in orienting visual attention, we sought to study this eye movement in young children to provide insights on face perception. For this purpose, we measured the modulation in the angle of eye vergence in a sample of 39 children aged 6-36 months and compared it when presenting static human face images versus their scrambled version. We observed enhanced vergence responses to faces compared with scrambled images. Our data suggest a role of eye vergence in face processing.

Early career researchers want Open Science.

Open Science is encouraged by the European Union and many other political and scientific institutions. However, scientific practice is proving slow to change. We propose, as early career researchers, that it is our task to change scientific research into open scientific research and commit to Open Science principles.

Astrocytic IL-6 mediates locomotor activity, exploration, anxiety, learning and social behavior.

Interleukin-6 (IL-6) is a major cytokine in the central nervous system, secreted by different brain cells and with roles in a number of physiological functions. We herewith confirm and expand the importance of astrocytic production of and response to IL-6 by using transgenic mice deficient in astrocytic IL-6 (Ast-IL-6 KO) or in its receptor (Ast-IL-6R KO) in full C57Bl/6 genetic background. A major prosurvival effect of astrocytic IL-6 at early ages was clearly demonstrated. Robust effects were also evident in the control of activity and anxiety in the hole-board and elevated plus-maze, and in spatial learning in the Morris water-maze. The results also suggest an inhibitory role of IL-6 in the mechanism controlling the consolidation of hippocampus-dependent spatial learning. Less robust effects of astrocytic IL-6 system were also observed in despair behavior in the tail suspension test, and social behavior in the dominance and resident-intruder tests. The behavioral phenotype was highly dependent on age and/or sex in some cases. The phenotype of Ast-IL-6R KO mice mimicked only partially that of Ast-IL-6KO mice, which indicates both a role of astrocytes in behavior and the participation of other cells besides astrocytes. No evidences of altered function of the hypothalamic-pituitary-adrenal axis were observed. These results demonstrate that astrocytic IL-6 (acting at least partially in astrocytes) regulates normal behavior in mice.