心尖肥厚型心肌病的临床特征及治疗

目的:总结心尖肥厚型心肌病的临床特征及治疗方法.方法:回顾性分析我院2008年6月至2012年2月期间经心脏超声或左室造影证实的33例心尖肥厚型心肌病患者的临床特征及治疗情况.结果:患者的临床症状表现为以胸闷、气短为主者20例;心前区不适4例;心前区疼痛5例;乏力2例;心悸l例;发现心电图异常前来就诊l例.32例患者行左室造影诊断为心尖肥厚型心肌病.l例因肾功能不全,未行左室造影,但经心脏超声诊断为心尖肥厚型心肌病.27例患者服用β-受体阻滞剂,2例患者服用钙离子拮抗剂,4例患者因心率慢,未服用药物,临床随访1～36(平均16.7± 4.1)个月,临床症状均明显缓解.结论:β-受体阻滞剂和钙离子拮抗剂均适用于治疗心尖肥厚型心肌病.     

Mutations in the gene encoding 3-hydroxyisobutyryl-CoA hydrolase results in progressive infantile neurodegeneration

Only a single patient with 3-hydroxyisobutyryl-CoA hydrolase deficiency has been described in the literature, and the molecular basis of this inborn error of valine catabolism has remained unknown until now. Here, we present a second patient with 3-hydroxyisobutyryl-CoA hydrolase deficiency, who was identified through blood spot acylcarnitine analysis showing persistently increased levels of hydroxy-C(4)-carnitine. Both patients manifested hypotonia, poor feeding, motor delay, and subsequent neurological regression in infancy. Additional features in the newly identified patient included episodes of ketoacidosis and Leigh-like changes in the basal ganglia on a magnetic resonance imaging scan. In cultured skin fibroblasts from both patients, the 3-hydroxyisobutyryl-CoA hydrolase activity was deficient, and virtually no 3-hydroxyisobutyryl-CoA hydrolase protein could be detected by western blotting. Molecular analysis in both patients uncovered mutations in the HIBCH gene, including one missense mutation in a conserved part of the protein and two mutations affecting splicing. A carefully interpreted acylcarnitine profile will allow more patients with 3-hydroxyisobutyryl-CoA hydrolase deficiency to be diagnosed.     

Quantitative analysis of variability of electrocardiograms typical for polymorphic arrhythmias

A new approach to the analysis of variability of electrocardiograms (ECGs) typical of polymorphic arrhythmias is developed. In these ECGs, separate QRS complexes can be often hardly identified. As a result, the mathematical methods that have been elaborated hitherto are not suitable for such arrhythmias. The approach presented here is based on the quantitative estimation of the variability of neighboring parts of the ECG. In this case, the necessity of the identification of separate QRS complexes ceases to be significant. Based on this approach, the analysis of normalized ECG variability is developed in the framework of which two indices that characterize the oscillation variability and its changes in time are related to a part of the ECG and/or the ECG as a whole. Variations of these indices allow both the polymorphism of a separate ECG to be estimated and different ECGs to be compared with each other. The method presented may be useful in studies of the mechanisms and in the diagnosis of polymorphic arrhythmias.     

Advances in the voltammetric analysis of small biologically relevant compounds

The problems associated with attempting to apply voltammetric techniques to the analysis of biologically relevant organics within complex media are identified and, through reviewing the very recent literature (1999-mid-2001), possible solutions are described. The boundaries of the search were limited to research targeted at the resolution of specific problems, associated with quantitative determinations. Various strategies have emerged to counter problems of poor sensitivity and selectivity and these have been summarized and critically appraised. Where possible, the characteristics of each approach have been distilled into a table format to ease comparison. Emphasis has been placed on the collation of information that will improve the intrinsic electrode response and as such should be of value to those interested in pursuing electroanalytical methodologies regardless of context.     

An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes

Electrocardiogram (ECG) signals are difficult to interpret, and clinicians must undertake a long training process to learn to diagnose diabetes from subtle abnormalities in these signals. To facilitate these diagnoses, we have developed a technique based on the heart rate variability signal obtained from ECG signals. This technique uses digital signal processing methods and, therefore, automates the detection of diabetes from ECG signals. In this paper, we describe the signal processing techniques that extract features from heart rate (HR) signals and present an analysis procedure that uses these features to diagnose diabetes. Through statistical analysis, we have identified the correlation dimension, Poincaré geometry properties (SD2), and recurrence plot properties (REC, DET, L _mean) as useful features. These features differentiate the HR data of diabetic patients from those of patients who do not have the illness, and have been validated by using the AdaBoost classifier with the perceptron weak learner (yielding a classification accuracy of 86%). We then developed a novel diabetic integrated index (DII) that is a combination of these nonlinear features. The DII indicates whether a particular HR signal was taken from a person with diabetes. This index aids the automatic detection of diabetes, thereby allowing a more objective assessment and freeing medical professionals for other tasks.     

Computer automated structure evaluation (CASE): a study of inhibitors of the thermolysin enzyme

The Computer Automated Structure Evaluation (CASE) program has been applied to the analysis of the inhibition of the thermolysin enzyme by derivatives of di- and poly-peptides. The inhibition constant ki, was used as a measure of the activity of the inhibitors. The program successfully identified molecular fragments relevant to the inhibitory activity of the peptides, without any assumption regarding the mechanism of inhibitory action. Utilizing these major fragments, Quantitative Structure Activity Relationship (QSAR) calculations were performed yielding a multiple linear regression equation for the prediction of inhibitory activity. A comparison of the conclusions reported in the literature regarding the structural features involved in the inhibition of thermolysin with the major fragments identified by the program is also made.     

Release patterns of copeptin and troponin in Tako-Tsubo cardiomyopathy

Copeptin, in addition to troponin, has recently been suggested for non-invasive differentiation between Tako-Tsubo cardiomyopathy (TTC) and acute myocardial infarction (AMI). In order to test this hypothesis, we investigated release patterns of pituitary copeptin and cardiac troponin in 49 patients with TTC and 49 age-, gender-, and ECG-matched control patients with AMI. Elevated copeptin levels (i.e. >12 pmol/l) at cardiac catheterization were found in 23/49 (47%) TTC patients and 25/49 (51%) AMI patients. Of these, median copeptin levels were almost identical in both cohorts (34.1 vs. 35.4 pmol/l). Subgroup analysis according to ECG changes revealed that AMI patients with ST-segment elevation had 3.6-fold higher copeptin levels than AMI patients without ST-segment elevation (p<0.05). Furthermore, in patients with TTC and atypical (midventricular) ballooning on left ventricular angiography, copeptin levels were 5.7-fold higher than in TTC patients with a typical (apical) type of ballooning (p<0.01). Elevated troponin T levels (i.e. >0.01 μg/l) at catheterization were detectable in 47/49 (96%) TTC patients and 45/49 (92%) AMI patients; however, peak levels did not differ significantly between both cohorts (median 0.35 vs. 0.27 μg/l). Subgroup analysis according to ECG changes revealed 2-fold higher peak troponin T levels in TTC patients presenting with ST-segment elevation than non-ST-segment elevation (p<0.05). In conclusion, copeptin does not seem to significantly increase non-invasive differentiation between TTC and AMI. At present, coronary angiography, specifically in patients with ST-segment elevation at presentation remains absolutely mandatory.     

Hypotheses generation as supervised link discovery with automated class labeling on large-scale biomedical concept networks

Computational approaches to generate hypotheses from biomedical literature have been studied intensively in recent years. Nevertheless, it still remains a challenge to automatically discover novel, cross-silo biomedical hypotheses from large-scale literature repositories. In order to address this challenge, we first model a biomedical literature repository as a comprehensive network of biomedical concepts and formulate hypotheses generation as a process of link discovery on the concept network. We extract the relevant information from the biomedical literature corpus and generate a concept network and concept-author map on a cluster using Map-Reduce frame-work. We extract a set of heterogeneous features such as random walk based features, neighborhood features and common author features. The potential number of links to consider for the possibility of link discovery is large in our concept network and to address the scalability problem, the features from a concept network are extracted using a cluster with Map-Reduce framework. We further model link discovery as a classification problem carried out on a training data set automatically extracted from two network snapshots taken in two consecutive time duration. A set of heterogeneous features, which cover both topological and semantic features derived from the concept network, have been studied with respect to their impacts on the accuracy of the proposed supervised link discovery process. A case study of hypotheses generation based on the proposed method has been presented in the paper.     

Aspects of neural plasticity in the central nervous system—I. Computer-assisted image analysis methods

Microdensitometric and morphometric techniques have been developed to quantitatively characterize cell groups and terminal populations of transmitter-identified neuronal systems. Various microdensitometric methods implemented on the image analyzer or on the scanning microdensitometer were introduced and compared. On this basis a technique to assess the half-life of dopamine stores determined by quantitative immunocytochemistry has been developed. The problem of relative and absolute quantification of microdensitometric analysis of immunocytochemical preparations is discussed here. A method has been developed for the study, both in 2- and 3-dimensions, of the overall features of the profile distribution in a defined neuroanatomical area. An approach to determine the degree of uniformity of a certain profile distribution is also proposed. Furthermore, methods for the evaluation of the codistribution of two or more different types of profiles and to characterize the morphometric features of patches of profiles in a certain region are presented. All these quantitative morphological approaches were tested in relevant preparations of the central nervous system.     

The computational analysis of scientific literature to define and recognize gene expression clusters

A limitation of many gene expression analytic approaches is that they do not incorporate comprehensive background knowledge about the genes into the analysis. We present a computational method that leverages the peer-reviewed literature in the automatic analysis of gene expression data sets. Including the literature in the analysis of gene expression data offers an opportunity to incorporate functional information about the genes when defining expression clusters. We have created a method that associates gene expression profiles with known biological functions. Our method has two steps. First, we apply hierarchical clustering to the given gene expression data set. Secondly, we use text from abstracts about genes to (i) resolve hierarchical cluster boundaries to optimize the functional coherence of the clusters and (ii) recognize those clusters that are most functionally coherent. In the case where a gene has not been investigated and therefore lacks primary literature, articles about well-studied homologous genes are added as references. We apply our method to two large gene expression data sets with different properties. The first contains measurements for a subset of well-studied Saccharomyces cerevisiae genes with multiple literature references, and the second contains newly discovered genes in Drosophila melanogaster; many have no literature references at all. In both cases, we are able to rapidly define and identify the biologically relevant gene expression profiles without manual intervention. In both cases, we identified novel clusters that were not noted by the original investigators.     

Phenotypic correlations in a patient with ring chromosome 22

Ring chromosome 22, a rare cytogenetic anomaly, has been described in over 60 cases in the medical literature. The aim of this report was to present a case carrying ring chromosome 22, and her family.It is a case report of a patient presented at Medical Faculty of ?ukurova University in Turkey.An 8-year-old girl with ring chromosome 22 and her family were evaluated cytogenetically and clinically.A chromosome analysis of the proband revealed a de novo 46, XX, r(22)(p11.2;q13) karyotype. Our subject demonstrated the prominent features of this syndrome including profound mental retardation, language impairment, dysmorphic features, lack of speech, hyperactivity, and behavioral disorders.There is lack of consistency between the physical abnormalities that we observed in our subject and those observed for such patients in the literature. The wide range of manifestations observed in patients with this cytogenetic alteration is probably due to size differences in the deleted region.     

Myocardial Infarction Detection and Localization Using Optimal Features Based Lead Specific Approach

ObjectivesObjective of this paper is to present a reliable and accurate technique for Myocardial Infarction (MI) detection and localization.Material and methodsStationary wavelet transform has been used to decompose the ECG signal. Energy, entropy and slope based features were extracted at specific wavelet bands from selected lead of ECG. k-Nearest Neighbors (kNN) with Mahalanobis distance function has been used for classification. Sensitivity (Se), specificity (Sp), positive predictivity (+P), accuracy (Acc), and area under the receiver operating characteristics curve (AUC) analyzed over 200 subjects (52 health control, 148 with MI) from Physikalisch-Technische Bundesanstalt (PTB) database has been used for performance analysis. To handle the imbalanced data adaptive synthetic (ADASYN) sampling approach has been adopted.ResultsFor detection of MI, the proposed technique has shown an AUC = 0.99, Se = 98.62%, Sp = 99.40%, PPR = 99.41% and Acc = 99.00% using 12 top ranked features, extracted from multiple leads of ECG and AUC = 0.99, Se = 98.34%, Sp = 99.77%, PPR = 99.77% and Acc = 99.05% using 12 features extracted from a single ECG lead (i.e. lead V5). For localization of MI, the proposed technique has an AUC = 0.99, Se = 98.78%, Sp = 99.86%, PPR = 98.80%, and Acc = 99.76% using 5 top ranked features from multiple leads of ECG and AUC = 0.98, Se = 96.47%, Sp = 99.60%, PPR = 96.49% and Acc = 99.28% using 8 features extracted from a single ECG lead (i.e. lead V3).ConclusionThus for MI detection and localization, the proposed technique is independent of time-domain ECG fiducial markers and can work using specific leads of ECG.     

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.     

Risk biomarker assessment for breast cancer progression: replication precision of nuclear morphometry.

Nuclear morphometry is a method for quantitative measurement of histopathologic changes in the appearance of stained cell nuclei. Numerous studies have indicated that these assessments may provide clinically relevant information related to the degree of progression and malignant potential of breast neoplasia. Nuclear features are derived from computerized analysis of digitized microscope images, and a quantitative Feulgen stain for DNA was used. Features analyzed included: (1) DNA content; (2) nuclear size and shape; and (3) texture features, describing spatial features of chromatin distribution. In this study replicated measurements are described on a series of 54 breast carcinoma specimens of differing pathologic grades. Duplicate measurements were performed using two serial sections, which were processed and analyzed separately. The value of a single feature measurement, the nuclear area profile, was shown to be the strongest indicator of progression. A quantitative nuclear grade was derived and shown to be strongly correlated with not only the pathologic nuclear grade, but also with tubule formation, mitotic grade, and with the overall histopathologic grade. Analysis of replication precision showed that the standard methods of the histopathology laboratory, if practiced in a uniform manner, are sufficient to ensure reproducibility of these assessments. We argue that nuclear morphometry provides a standardized and reproducible framework for quantitative pathologic assessments.     

Only neutral polymorphisms found in the TIGR/myocilin gene of 45 Polish patients with primary open-angle glaucoma

The aim of the study was to identify mutations of the TIGR gene in Polish patients with primary open-angle glaucoma (POAG) and to define possible genotype-phenotype correlations. The study included 45 patients with a verified diagnosis of POAG. The PCR amplification of all three exons of the TIGR gene and screening for the sequence changes by CSGE analysis was done for every patient. The probes with identified heteroduplexes were sequenced. Altogether 315 PCR products were obtained. The CSGE analysis detected 60 possible changes of the sequence in 28 patients. 34 heteroduplexes were chosen for sequencing, including 29 unique changes and 5 changes representative of identical heteroduplexes. Direct sequencing enabled detection of only four different changes in the TIGR gene sequence. Three of them: 5'UTR -83G-->A (in 14 patients), +227 exon 1 G-->A, Arg76Lys (in 14 patients) and +311 exon 3 T-->C, Tyr347Tyr (in 4 patients) have already been described in the literature as neutral polymorphisms of the gene. Only one change in the promoter, 5'UTR -126T-->C (in 2 patients), has not been described in the literature to date. However, this change does not alter directly the sequence of amino acids in myocilin, so it is difficult to conclude on its pathogenetic role. Thus our study showed only neutral polymorphisms of the TIGR gene. This suggests that the patients probably have mutations in other genes, so other loci that predispose to POAG must be analyzed.     

Sequence analysis of the ribosome-protected bacteriophage φX174 DNA fragment containing the gene G initiation site

The nucleotide sequence of the principal bacteriophage φX174 ribosome-protected DNA fragment has been determined. Details of the approaches and methods used for direct DNA sequence analysis are described, The resulting sequence allows prediction of the first nine amino acids at the amino terminus of a protein which has been identified as the product of φX174 gene G. The sequence has several features of biological relevance including two termination codons to the left of the initiator triplet.     

Identification and characterization of sporadic and inherited mutations in exon 31 of the neurofibromatosis (NF1) gene

Neurofibromatosis type 1 (NF1) is one of the most common genetic disorders in humans, and presents with a variety of clinical symptoms, which are highly variable in expression. The mutation rate for NF1 is high, with as many as half of all cases resulting from new mutations. Although the NF1 gene has been cloned and its cDNA sequence determined, the specific role of the NF1 gene product in contributing to the NF1 phenotype has not been clarified. The characterization of NF1 mutations is one of the first steps in correlating genotype with clinical symptoms of the disease. In this paper we describe two independent mutations in exon 31 of the NF1 gene identified following polymerase chain reaction (PCR) amplification, heteroduplexing, and single strand conformational polymorphism (SSCP) analysis. One is a novel insertion that segregates with the disease phenotype in that particular family (5852insTT), while the other is a further example of the sporadic, recurrent CT mutation previously described in the literature (C5842T). The relationship between these mutations and clinical features of NF1 presented by the patients will be discussed.     

Characterizing the metabolic phenotype: a phenotype phase plane analysis.

Genome-scale metabolic maps can be reconstructed from annotated genome sequence data, biochemical literature, bioinformatic analysis, and strain-specific information. Flux-balance analysis has been useful for qualitative and quantitative analysis of metabolic reconstructions. In the past, FBA has typically been performed in one growth condition at a time, thus giving a limited view of the metabolic capabilities of a metabolic network. We have broadened the use of FBA to map the optimal metabolic flux distribution onto a single plane, which is defined by the availability of two key substrates. A finite number of qualitatively distinct patterns of metabolic pathway utilization were identified in this plane, dividing it into discrete phases. The characteristics of these distinct phases are interpreted using ratios of shadow prices in the form of isoclines. The isoclines can be used to classify the state of the metabolic network. This methodology gives rise to a "phase plane" analysis of the metabolic genotype-phenotype relation relevant for a range of growth conditions. Phenotype phase planes (PhPPs) were generated for Escherichia coli growth on two carbon sources (acetate and glucose) at all levels of oxygenation, and the resulting optimal metabolic phenotypes were studied. Supplementary information can be downloaded from our website (http://epicurus.che.udel.edu).     

Literature Review and Comparison of Two Statistical Methods to Evaluate the Effect of Botulinum Toxin Treatment on Gait in Children with Cerebral Palsy

Aim

This study aimed at comparing two statistical approaches to analyze the effect of Botulinum Toxin A (BTX-A) treatment on gait in children with a diagnosis of spastic cerebral palsy (CP), based on three-dimensional gait analysis (3DGA) data. Through a literature review, the available expert knowledge on gait changes after BTX-A treatment in children with CP is summarized.

Methods

Part 1—Intervention studies on BTX-A treatment in children with CP between 4–18 years that used 3DGA data as an outcome measure and were written in English, were identified through a broad systematic literature search. Reported kinematic and kinetic gait features were extracted from the identified studies. Part 2—A retrospective sample of 53 children with CP (6.1 ± 2.3years, GMFCS I-III) received 3DGA before and after multilevel BTX-A injections. The effect of BTX-A on gait was interpreted by comparing the results of paired samples t-tests on the kinematic gait features that were identified from literature to the results of statistical parametric mapping analysis on the kinematic waveforms of the lower limb joints.

Results

Part 1–53 kinematic and 33 kinetic features were described in literature. Overall, there is no consensus on which features should be evaluated after BTX-A treatment as 49 features were reported only once or twice. Part 2—Post-BTX-A, both statistical approaches found increased ankle dorsiflexion throughout the gait cycle. Statistical parametric mapping analyses additionally found increased knee extension during terminal stance. In turn, feature analyses found increased outtoeing during stance after BTX-A.

Conclusion

This study confirms that BTX-A injections are a valuable treatment option to improve gait function in children with CP. However, different statistical approaches may lead to different interpretations of treatment outcome. We suggest that a clear, definite hypothesis should be stated a priori and a commensurate statistical approach should accompany this hypothesis.