30 research outputs found
A novel SETD2 variant causing global development delay without overgrowth in a Chinese 3-year-old boy
Background: Luscan-Lumish syndrome is characterized by macrocephaly, postnatal overgrowth, intellectual disability (ID), developmental delay (DD), which is caused by heterozygous SETD2 (SET domain containing 2) mutations. The incidence of Luscan-Lumish syndrome is unclear. The study was conducted to provide a novel pathogenic SETD2 variant causing atypical Luscan-Lumish syndrome and review all the published SETD2 mutations and corresponding symptoms, comprehensively understanding the phenotypes and genotypes of SETD2 mutations.Methods: Peripheral blood samples of the proband and his parents were collected for next-generation sequencing including whole-exome sequencing (WES), copy number variation (CNV) detection and mitochondrial DNA sequencing. Identified variant was verified by Sanger sequencing. Conservative analysis and structural analysis were performed to investigate the effect of mutation. Public databases such as PubMed, Clinvar and Human Gene Mutation Database (HGMD) were used to collect all cases with SETD2 mutations.Results: A novel pathogenic SETD2 variant (c.5835_c.5836insAGAA, p. A1946Rfs*2) was identified in a Chinese 3-year-old boy, who had speech and motor delay without overgrowth. Conservative analysis and structural analysis showed that the novel pathogenic variant would loss the conserved domains in the C-terminal region and result in loss of function of SETD2 protein. Frameshift mutations and non-sense mutations account for 68.5% of the total 51 SETD2 point mutations, suggesting that Luscan-Lumish syndrome is likely due to loss of function of SETD2. But we failed to find an association between genotype and phenotype of SETD2 mutations.Conclusion: Our findings expand the genotype-phenotype knowledge of SETD2-associated neurological disorder and provide new evidence for further genetic counselling
Assessing the benthic ecological status in the stressed coastal waters of Yantai, Yellow Sea, using AMBI and M-AMBI
Analysis of the influence of the grounding method on the measurement of direct current total electric field on a civil housing platform
Abstract Buildings near direct current transmission lines are sensitive to the electromagnetic environment, and the measurement of the electric field above them is important in engineering design and environmental assessment in China. The models of buildings and probes in the ion flow field were established to explore the accurate measurement method of the electric field above the building. Based on the upstream finite element method and the predictorâcorrector method, the influence of whether the probe was grounded or not above the building was studied. On this basis, simulation experiments and realâtype experiments were carried out. The results show that when the electrical conductivity of the building was greater than 10â10 S/m, being grounded or not would not change the results. When the building conductivity was between 10â11 and 10â12 S/m, the electric field measurement results would be increased by 30% to 120% after grounding. In the realâtype experiments on the platform with a plywood roof, the relative error in the electric field when grounded or not was only 2.6%. This proved the reliability of the calculated results. In this paper, the measuring method of the DC space chargeâmodified electric field above buildings was analyzed first, and the conclusion that ground wire can be cancelled above buildings with general materials was presented. The research results can provide a technical basis for the accurate measurement of the electric field above the buildings near DC transmission lines
Sound Source Separation Mechanisms of Different Deep Networks Explained from the Perspective of Auditory Perception
Thanks to the development of deep learning, various sound source separation networks have been proposed and made significant progress. However, the study on the underlying separation mechanisms is still in its infancy. In this study, deep networks are explained from the perspective of auditory perception mechanisms. For separating two arbitrary sound sources from monaural recordings, three different networks with different parameters are trained and achieve excellent performances. The networksâ output can obtain an average scale-invariant signal-to-distortion ratio improvement (SI-SDRi) higher than 10 dB, comparable with the human performance to separate natural sources. More importantly, the most intuitive principleâproximityâis explored through simultaneous and sequential organization experiments. Results show that regardless of network structures and parameters, the proximity principle is learned spontaneously by all networks. If components are proximate in frequency or time, they are not easily separated by networks. Moreover, the frequency resolution at low frequencies is better than at high frequencies. These behavior characteristics of all three networks are highly consistent with those of the human auditory system, which implies that the learned proximity principle is not accidental, but the optimal strategy selected by networks and humans when facing the same task. The emergence of the auditory-like separation mechanisms provides the possibility to develop a universal system that can be adapted to all sources and scenes
Sound Source Separation Mechanisms of Different Deep Networks Explained from the Perspective of Auditory Perception
Thanks to the development of deep learning, various sound source separation networks have been proposed and made significant progress. However, the study on the underlying separation mechanisms is still in its infancy. In this study, deep networks are explained from the perspective of auditory perception mechanisms. For separating two arbitrary sound sources from monaural recordings, three different networks with different parameters are trained and achieve excellent performances. The networks’ output can obtain an average scale-invariant signal-to-distortion ratio improvement (SI-SDRi) higher than 10 dB, comparable with the human performance to separate natural sources. More importantly, the most intuitive principle—proximity—is explored through simultaneous and sequential organization experiments. Results show that regardless of network structures and parameters, the proximity principle is learned spontaneously by all networks. If components are proximate in frequency or time, they are not easily separated by networks. Moreover, the frequency resolution at low frequencies is better than at high frequencies. These behavior characteristics of all three networks are highly consistent with those of the human auditory system, which implies that the learned proximity principle is not accidental, but the optimal strategy selected by networks and humans when facing the same task. The emergence of the auditory-like separation mechanisms provides the possibility to develop a universal system that can be adapted to all sources and scenes
LowâPermittivity Copolymerized Polyimides with Fluorene Rigid Conjugated Structure
As the miniaturization of electronic appliances and microprocessors progresses, low-permittivity interlayer materials are becoming increasingly important for their suppression of electronic crosstalk, signal propagation delay and loss, and so forth. Herein, a kind of copolyimide (CPI) film with a âfluoreneâ rigid conjugated structure was prepared successfully. By introducing 9,9-Bis(3-fluoro-4-aminophenyl) fluorene as the rigid conjugated structure monomer, a series of CPI films with different molecular weights were fabricated by in situ polymerization, which not only achieved the reduction of permittivity but also maintained excellent thermodynamic stability. Moreover, the hydrophobicity of the CPI film was also improved with the increasing conjugated structure fraction. The lowest permittivity reached 2.53 at 106 Hz, while the thermal decomposition temperature (Td5%) was up to 530 °C, and the tensile strength was â„ 96 MPa. Thus, the CPI films are potential dielectric materials for microelectronic and insulation applications
Table1_A novel SETD2 variant causing global development delay without overgrowth in a Chinese 3-year-old boy.XLSX
Background: Luscan-Lumish syndrome is characterized by macrocephaly, postnatal overgrowth, intellectual disability (ID), developmental delay (DD), which is caused by heterozygous SETD2 (SET domain containing 2) mutations. The incidence of Luscan-Lumish syndrome is unclear. The study was conducted to provide a novel pathogenic SETD2 variant causing atypical Luscan-Lumish syndrome and review all the published SETD2 mutations and corresponding symptoms, comprehensively understanding the phenotypes and genotypes of SETD2 mutations.Methods: Peripheral blood samples of the proband and his parents were collected for next-generation sequencing including whole-exome sequencing (WES), copy number variation (CNV) detection and mitochondrial DNA sequencing. Identified variant was verified by Sanger sequencing. Conservative analysis and structural analysis were performed to investigate the effect of mutation. Public databases such as PubMed, Clinvar and Human Gene Mutation Database (HGMD) were used to collect all cases with SETD2 mutations.Results: A novel pathogenic SETD2 variant (c.5835_c.5836insAGAA, p. A1946Rfs*2) was identified in a Chinese 3-year-old boy, who had speech and motor delay without overgrowth. Conservative analysis and structural analysis showed that the novel pathogenic variant would loss the conserved domains in the C-terminal region and result in loss of function of SETD2 protein. Frameshift mutations and non-sense mutations account for 68.5% of the total 51 SETD2 point mutations, suggesting that Luscan-Lumish syndrome is likely due to loss of function of SETD2. But we failed to find an association between genotype and phenotype of SETD2 mutations.Conclusion: Our findings expand the genotype-phenotype knowledge of SETD2-associated neurological disorder and provide new evidence for further genetic counselling.</p