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1.
Background
Learning Disorders (LD) are complex diseases that affect about 2-10% of the school-age population. We performed neuropsychological and psychopathological evaluation, in order to investigate comorbidity in children with LD.Methods
Our sample consisted of 448 patients from 7 to 16 years of age with a diagnosis of LD, divided in two subgroups: Specific Learning Disorders (SLD), including reading, writing, mathematics disorders, and Learning Disorders Not Otherwise Specified (LD NOS).Results
Comorbidity with neuropsychopathologies was found in 62.2% of the total sample. In the LSD subgroup, ADHD was present in 33%, Anxiety Disorder in 28.8%, Developmental Coordination Disorder in 17.8%, Language Disorder in 11% and Mood Disorder in 9.4% of patients. In LD NOS subgroup, Language Disorder was present in 28.6%, Developmental Coordination Disorder in 27.5%, ADHD in 25.4%, Anxiety Disorder in 16.4%, Mood Disorder in 2.1% of patients. A statistically significant presence was respectively found for Language and Developmental Coordination Disorder comorbidity in LD NOS and for ADHD, mood and anxiety disorder comorbidity in SLD subgroup.Conclusions
The different findings emerging in this study suggested to promote further investigations to better define the difference between SLD and LD NOS, in order to improve specific interventions to reduce the long range consequences.2.
Andreas Mueller Gian Candrian Juri D Kropotov Valery A Ponomarev Gian-Marco Baschera 《Nonlinear biomedical physics》2010,4(Z1):S1
Background
In the context of sensory and cognitive-processing deficits in ADHD patients, there is considerable evidence of altered event related potentials (ERP). Most of the studies, however, were done on ADHD children. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. Using the classification method of support vector machine, this study investigated whether features of independent ERP components can be used for discrimination of ADHD adults from healthy subjects.Methods
Two groups of age- and sex-matched adults (74 ADHD, 74 controls) performed a visual two stimulus GO/NOGO task. ERP responses were decomposed into independent components by means of ICA. A feature selection algorithm defined a set of independent component features which was entered into a support vector machine.Results
The feature set consisted of five latency measures in specific time windows, which were collected from four different independent components. The independent components involved were a novelty component, a sensory related and two executive function related components. Using a 10-fold cross-validation approach, classification accuracy was 92%.Conclusions
This study was a first attempt to classify ADHD adults by means of support vector machine which indicates that classification by means of non-linear methods is feasible in the context of clinical groups. Further, independent ERP components have been shown to provide features that can be used for characterizing clinical populations.3.
Athanasios Tragiannidis Zoe Dorothea Pana Theodotis Papageorgiou Emmanuel Hatzipantelis Maria Hatzistilianou Fani Athanassiadou 《Journal of medical case reports》2011,5(1):407
Introduction
Transient myeloproliferative disorder is a hematologic abnormality characterized by an uncontrolled proliferation of myeloblasts in peripheral blood and bone marrow that primarily affects newborns and babies with Down syndrome. Tumor lysis syndrome is rarely associated with transient myeloproliferative disorder.Case presentation
Transient myeloproliferative disorder was diagnosed in a seven-day-old baby girl with Down syndrome, who was referred to our department due to hyperleukocytosis. Our patient developed tumor lysis syndrome, successfully treated with rasburicase, as a complication of transient myeloproliferative disorder resulting from rapid degradation of myeloid blasts after initiation of effective chemotherapy.Conclusions
Tumor lysis syndrome is rarely reported as a complication of transient myeloproliferative disorder. To the best of our knowledge, this is the first case of a newborn with Down syndrome and transient myeloproliferative disorder treated with rasburicase for developing tumor lysis syndrome.4.
Haresh Devalia Anushka Chaudhry Richard M Rainsbury Neda Minakaran Dibyesh Banerjee 《International Seminars in Surgical Oncology : ISSO》2007,4(1):29
Background
Lateral skin folds or 'dog-ears' are frequent following mastectomy, particularly in patients with large body habitus.Methods
We describe a method of modifying the mastectomy incision and suturing to eliminate these lateral 'dog-ears'.Conclusion
This surgical technique, as compared to others described in the literature, is simple, does not require additional incisions and is cosmetically acceptable to the patient.5.
N. Cesbron A.-L. Royer Y. Guitton A. Sydor B. Le Bizec G. Dervilly-Pinel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):99
Introduction
Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.Objectives
In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.Methods
The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.Results
A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.Conclusion
The workflow generated repeatable and informative fingerprints for robust metabolome characterization.6.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.7.
Tie-juan Shao Zhi-xing He Zhi-jun Xie Hai-chang Li Mei-jiao Wang Cheng-ping Wen 《Metabolomics : Official journal of the Metabolomic Society》2016,12(4):70
Introduction
The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.Objectives
The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.Methods
Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by 1H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.Results
Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.Conclusion
The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by 1H NMR metabolomics.8.
Sonia Liggi Christine Hinz Zoe Hall Maria Laura Santoru Simone Poddighe John Fjeldsted Luigi Atzori Julian L. Griffin 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):52
Introduction
Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.Objectives
Merge in the same platform the steps required for metabolomics data processing.Methods
KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.Results
The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.Conclusion
KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.9.
Introduction
Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.Objectives
Assessment of the quality of raw data processing in untargeted metabolomics.Methods
Five published untargeted metabolomics studies, were reanalyzed.Results
Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.Conclusion
Incomplete raw data processing shows unexplored potential of current and legacy data.10.
Background
Studies of intrinsically disordered proteins that lack a stable tertiary structure but still have important biological functions critically rely on computational methods that predict this property based on sequence information. Although a number of fairly successful models for prediction of protein disorder have been developed over the last decade, the quality of their predictions is limited by available cases of confirmed disorders.Results
To more reliably estimate protein disorder from protein sequences, an iterative algorithm is proposed that integrates predictions of multiple disorder models without relying on any protein sequences with confirmed disorder annotation. The iterative method alternately provides the maximum a posterior (MAP) estimation of disorder prediction and the maximum-likelihood (ML) estimation of quality of multiple disorder predictors. Experiments on data used at CASP7, CASP8, and CASP9 have shown the effectiveness of the proposed algorithm.Conclusions
The proposed algorithm can potentially be used to predict protein disorder and provide helpful suggestions on choosing suitable disorder predictors for unknown protein sequences.11.
Ferran Casbas Pinto Srinivarao Ravipati David A. Barrett T. Charles Hodgman 《Metabolomics : Official journal of the Metabolomic Society》2017,13(7):81
Introduction
It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.Objectives
This work simplifies this process.Methods
A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.Results
The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.Conclusion
This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.12.
Background
In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.Methods
The physical basis of these intuitive maps is clarified by means of analytically solvable problems.Results
Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.Conclusion
Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.13.
Background
Intrinsically disordered proteins (IDPs) and regions (IDRs) perform a variety of crucial biological functions despite lacking stable tertiary structure under physiological conditions in vitro. State-of-the-art sequence-based predictors of intrinsic disorder are achieving per-residue accuracies over 80%. In a genome-wide study of intrinsic disorder in human genome we observed a big difference in predicted disorder content between confirmed and putative human proteins. We investigated a hypothesis that this discrepancy is not correct, and that it is due to incorrectly annotated parts of the putative protein sequences that exhibit some similarities to confirmed IDRs, which lead to high predicted disorder content.Methods
To test this hypothesis we trained a predictor to discriminate sequences of real proteins from synthetic sequences that mimic errors of gene finding algorithms. We developed a procedure to create synthetic peptide sequences by translation of non-coding regions of genomic sequences and translation of coding regions with incorrect codon alignment.Results
Application of the developed predictor to putative human protein sequences showed that they contain a substantial fraction of incorrectly assigned regions. These regions are predicted to have higher levels of disorder content than correctly assigned regions. This partially, albeit not completely, explains the observed discrepancy in predicted disorder content between confirmed and putative human proteins.Conclusions
Our findings provide the first evidence that current practice of predicting disorder content in putative sequences should be reconsidered, as such estimates may be biased.14.
Karimeh Haghani Pouyan Asadi Gholamreza Taheripak Ali Noori-Zadeh Shahram Darabi Salar Bakhtiyari 《生物学前沿》2018,13(6):406-417
Background
Diabetes mellitus (DM) is one of the most prevalent chronic diseases, and its prevalence continues to increase globally. The impact of mitochondrial dysfunction and lipid metabolism on diabetes mellitus and insulin resistance (IR) has been implicated in several previous reports; however, the results of studies are confusing despite four decades of study.Methods/Results
This review has evaluated updated understanding of the role of mitochondrial dysfunction and lipid metabolism on type 2 diabetes, and found that mitochondrial dysfunction and lipid metabolism disorder induce the dysregulation of liver and pancreatic beta cells, insulin resistance, and type 2 diabetes.Conclusion
Mitochondrial dysfunction and lipid metabolism induce metabolic dysregulation and finally increasing the possibility of diabetes.15.
Renato de Souza Pinto Lemgruber Kaspar Valgepea Mark P. Hodson Ryan Tappel Sean D. Simpson Michael Köpke Lars K. Nielsen Esteban Marcellin 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):35
Introduction
Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.Objective
To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.Methods
Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.Results
Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.Conclusion
Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.16.
Jamie V. de Seymour Stephanie Tu Xiaoling He Hua Zhang Ting-Li Han Philip N. Baker Karolina Sulek 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):79
Introduction
Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.Objective
Investigate the maternal hair metabolome for predictive biomarkers of ICP.Methods
The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.Results
Of 105 metabolites detected in hair, none were significantly associated with ICP.Conclusion
Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.17.
Thijs Welle Anna T. Hoekstra Ineke A. J. J. M. Daemen Celia R. Berkers Matheus O. Costa 《Metabolomics : Official journal of the Metabolomic Society》2017,13(7):83
Introduction
Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.Objective
The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.Methods
Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.Results
Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.Conclusions
The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.18.
Background
Primary angiitis of the central nervous system is an idiopathic disorder characterized by vasculitis within the dural confines. The clinical presentation shows a wide variation and the course and the duration of disease are heterogeneous. This rare but treatable disease provides a diagnostic challenge owing to the lack of pathognomonic tests and the necessity of a histological confirmation.Case presentation
A 28-year-old patient presenting with headache and fluctuating signs of encephalopathy was treated on the assumption of viral meningoencephalitis. The course of the disease led to his death 10 days after hospital admission. Postmortem examination revealed primary angiitis of the central nervous system.Conclusion
Primary angiitis of the central nervous system should always be taken into consideration when suspected infectious inflammation of the central nervous system does not respond to treatment adequately. In order to confirm the diagnosis with the consequence of a modified therapy angiography and combined leptomeningeal and brain biopsy should be considered immediately.19.
Nicholas J. Bond Albert Koulman Julian L. Griffin Zoe Hall 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):128
Introduction
Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.Objectives
We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.Methods
massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.Results
Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.Conclusion
massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.20.
Miriam Banas Sindy Neumann Johannes Eiglsperger Eric Schiffer Franz Josef Putz Simone Reichelt-Wurm Bernhard Karl Krämer Philipp Pagel Bernhard Banas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(9):116