Association of the rs3743205 variant of DYX1C1 with dyslexia in Chinese children

<p>Abstract</p> <p><b>Background</b></p> <p>Dyslexia is a learning disability that is characterized by difficulties in the acquisition of reading and spelling skills independent of intelligence, motivation or schooling. Studies of western populations have suggested that <it>DYX1C1 </it>is a candidate gene for dyslexia. In view of the different languages used in Caucasian and Chinese populations, it is therefore worthwhile to investigate whether there is an association of <it>DYX1C1 </it>in Chinese children with dyslexia.</p> <p>Method and Results</p> <p>Eight single nucleotide polymorphisms (SNPs) were genotyped from three hundred and ninety three individuals from 131 Chinese families with two which have been reported in the literature and six tag SNPs at <it>DYX1C1</it>. Analysis for allelic and haplotypic associations was performed with the UNPHASED program and multiple testing was corrected using false discovery rates. We replicated the previously reported association of rs3743205 in Chinese children with dyslexia (<it>p</it>_{<it>corrected </it>}= 0.0072). This SNP was also associated with rapid naming, phonological memory and orthographic skills in quantitative trait analysis.</p> <p>Conclusion</p> <p>Our findings suggest that <it>DYX1C1 </it>is associated with dyslexia in people of Chinese ethnicity in Hong Kong.</p

Time evolution in linear response: Boltzmann equations and beyond

In this work a perturbative linear response analysis is performed for the time evolution of the quasi-conserved charge of a scalar field. One can find two regimes, one follows exponential damping, where the damping rate is shown to come from quantum Boltzmann equations. The other regime (coming from multiparticle cuts and products of them) decays as power law. The most important, non-oscillating contribution in our model comes from a 4-particle intermediate state and decays as 1/t^3. These results may have relevance for instance in the context of lepton number violation in the Early Universe.Comment: 19 page

Methionine Adenosyltransferase I/III Deficiency in Portugal: High Frequency of a Dominantly Inherited Form in a Small Area of Douro High Lands

Methionine adenosyltransferase deficienc(MAT I/III deficiency) is an inborn error of metabolism resulting in isolated hypermethioninemia, and usually inherited as an autosomal recessive trait, although a dominant form has been reported in several families. During the last 6 years, approximately 520,000 newborns were screened in the Portuguese Newborn Screening Laboratory by MS/MS, and 21 cases of persistent hypermethioninemia were found. One case was confirmed to be a deficiency of cystathionine b-synthase and 20 cases were confirmed by MAT1A gene analysis to have an elevation of methionine due to MAT I/III deficiency, which indicates an incidence for this condition of 1/26,000. Twelve of the MAT I/III deficient newborns, belonging to 11 families, were identified in the northern region of Portugal and sent to the same treatment center, where they are under follow-up. Clinical, biochemical, and genetic characteristics of individuals from these 11 families are presented. Plasma methionine and homocysteine concentrations were found to be moderately increased in all newborns, and molecular analysis revealed that they all were heterozygous for R264H mutation. Normal growth,development, and neurological examination were observed in all cases, and cerebral MRI performed in six cases revealed myelination abnormalities in one case. Plasma methionine concentration for all 12 cases was always below 300 mM, and they are all on a normal diet for their age

Analysis and Prediction of the Metabolic Stability of Proteins Based on Their Sequential Features, Subcellular Locations and Interaction Networks

The metabolic stability is a very important idiosyncracy of proteins that is related to their global flexibility, intramolecular fluctuations, various internal dynamic processes, as well as many marvelous biological functions. Determination of protein's metabolic stability would provide us with useful information for in-depth understanding of the dynamic action mechanisms of proteins. Although several experimental methods have been developed to measure protein's metabolic stability, they are time-consuming and more expensive. Reported in this paper is a computational method, which is featured by (1) integrating various properties of proteins, such as biochemical and physicochemical properties, subcellular locations, network properties and protein complex property, (2) using the mRMR (Maximum Relevance & Minimum Redundancy) principle and the IFS (Incremental Feature Selection) procedure to optimize the prediction engine, and (3) being able to identify proteins among the four types: “short”, “medium”, “long”, and “extra-long” half-life spans. It was revealed through our analysis that the following seven characters played major roles in determining the stability of proteins: (1) KEGG enrichment scores of the protein and its neighbors in network, (2) subcellular locations, (3) polarity, (4) amino acids composition, (5) hydrophobicity, (6) secondary structure propensity, and (7) the number of protein complexes the protein involved. It was observed that there was an intriguing correlation between the predicted metabolic stability of some proteins and the real half-life of the drugs designed to target them. These findings might provide useful insights for designing protein-stability-relevant drugs. The computational method can also be used as a large-scale tool for annotating the metabolic stability for the avalanche of protein sequences generated in the post-genomic age

MemBrain: Improving the Accuracy of Predicting Transmembrane Helices

Prediction of transmembrane helices (TMH) in α helical membrane proteins provides valuable information about the protein topology when the high resolution structures are not available. Many predictors have been developed based on either amino acid hydrophobicity scale or pure statistical approaches. While these predictors perform reasonably well in identifying the number of TMHs in a protein, they are generally inaccurate in predicting the ends of TMHs, or TMHs of unusual length. To improve the accuracy of TMH detection, we developed a machine-learning based predictor, MemBrain, which integrates a number of modern bioinformatics approaches including sequence representation by multiple sequence alignment matrix, the optimized evidence-theoretic K-nearest neighbor prediction algorithm, fusion of multiple prediction window sizes, and classification by dynamic threshold. MemBrain demonstrates an overall improvement of about 20% in prediction accuracy, particularly, in predicting the ends of TMHs and TMHs that are shorter than 15 residues. It also has the capability to detect N-terminal signal peptides. The MemBrain predictor is a useful sequence-based analysis tool for functional and structural characterization of helical membrane proteins; it is freely available at http://chou.med.harvard.edu/bioinf/MemBrain/

Record linkage research and informed consent: who consents?

BACKGROUND: Linking computerized health insurance records with routinely collected survey data is becoming increasingly popular in health services research. However, if consent is not universal, the requirement of written informed consent may introduce a number of research biases. The participants of a national health survey in Taiwan were asked to have their questionnaire results linked to their national health insurance records. This study compares those who consented with those who refused. METHODS: A national representative sample (n = 14,611 adults) of the general adult population aged 20 years or older who participated in the Taiwan National Health Interview Survey (NHIS) and who provided complete survey information were used in this study. At the end of the survey, the respondents were asked if they would give permission to access their National Health Insurance records. Information given by the interviewees in the survey was used to analyze who was more likely to consent to linkage and who wasn't. RESULTS: Of the 14,611 NHIS participants, 12,911 (88%) gave consent, and 1,700 (12%) denied consent. The elderly, the illiterate, those with a lower income, and the suburban area residents were significantly more likely to deny consent. The aborigines were significantly less likely to refuse. No discrepancy in gender and self-reported health was found between individuals who consented and those who refused. CONCLUSION: This study is the first population-based study in assessing the consent pattern in a general Asian population. Consistent with people in Western societies, in Taiwan, a typical Asian society, a high percentage of adults gave consent for their health insurance records and questionnaire results to be linked. Consenters differed significantly from non-consenters in important aspects such as age, ethnicity, and educational background. Consequently, having a high consent rate (88%) may not fully eliminate the possibility of selection bias. Researchers should take this source of bias into consideration in their study design and investigate any potential impact of this source of bias on their results

Three-dimensionally Ordered Macroporous Structure Enabled Nanothermite Membrane of Mn2O3/Al

Mn2O3 has been selected to realize nanothermite membrane for the first time in the literature. Mn2O3/Al nanothermite has been synthesized by magnetron sputtering a layer of Al film onto three-dimensionally ordered macroporous (3DOM) Mn2O3 skeleton. The energy release is significantly enhanced owing to the unusual 3DOM structure, which ensures Al and Mn2O3 to integrate compactly in nanoscale and greatly increase effective contact area. The morphology and DSC curve of the nanothermite membrane have been investigated at various aluminizing times. At the optimized aluminizing time of 30 min, energy release reaches a maximum of 2.09 kJ∙g−1, where the Al layer thickness plays a decisive role in the total energy release. This method possesses advantages of high compatibility with MEMS and can be applied to other nanothermite systems easily, which will make great contribution to little-known nanothermite research

Selective patterning of ZnO nanorods on silicon substrates using nanoimprint lithography

In this research, nanoimprint lithography (NIL) was used for patterning crystalline zinc oxide (ZnO) nanorods on the silicon substrate. To fabricate nano-patterned ZnO nanorods, patterning of an n-octadecyltrichlorosilane (OTS) self-assembled monolayers (SAMs) on SiO2 substrate was prepared by the polymer mask using NI. The ZnO seed layer was selectively coated only on the hydrophilic SiO2 surface, not on the hydrophobic OTS SAMs surface. The substrate patterned with the ZnO seed layer was treated with the oxygen plasma to oxidize the silicon surface. It was found that the nucleation and initial growth of the crystalline ZnO were proceeded only on the ZnO seed layer, not on the silicon oxide surface. ZnO photoluminescence spectra showed that ZnO nanorods grown from the seed layer treated with plasma showed lower intensity than those untreated with plasma at 378 nm, but higher intensity at 605 nm. It is indicated that the seed layer treated with plasma produced ZnO nanorods that had a more oxygen vacancy than those grown from seed layer untreated with plasma. Since the oxygen vacancies on ZnO nanorods serve as strong binding sites for absorption of various organic and inorganic molecules. Consequently, a nano-patterning of the crystalline ZnO nanorods grown from the seed layer treated with plasma may give the versatile applications for the electronics devices

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

© 2017 The Author(s). Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis