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Introduction:Germline pathogenic variations of the genes encoding the components of the Ras-MAPK pathway are found to be responsible for RASopathies, a clinically and genetically heterogeneous group of diseases. In this study, we aimed to present the results of patients genetically investigated for RASopathy-related mutations in our Genetic Diagnosis Center. Methods:The results of 51 unrelated probands with RASopathy and 4 affected relatives (31 male, 24 female; mean age: 9.327 ± 8.214) were included in this study. Mutation screening was performed on DNA samples from peripheral blood of the patients either by Sanger sequencing of PTPN11hotspot regions (10/51 probands), or by a targeted amplicon next-generation sequencing panel (41/51 probands) covering the exonic regions of BRAF, CBL, HRAS, KRAS, LZTR1, MAP2K1, MAP2K2, NF1, NRAS, PTPN11, RAF1, RASA2, RIT1, SHOC2, SOS1, SOS2, SPRED1, and KAT6Bgenes. Results:Pathogenic/likely pathogenic variations found in 22 out of 51 probands (43.13%) and their 4 affected family members were located in PTPN11, BRAF, KRAS, NF1, RAF1, SOS1, and SHOC2genes. The c.148A>C (p.Thr50Pro) variation in the KRASgene was a novel variant detected in a sibling in our patient cohort. We found supportive evidence for the pathogenicity of the NF1gene c.5606G>T (p.Gly1869Val) variation which we defined in an affected boy who inherited the mutation from his affected father. Conclusion:Although PTPN11is the most frequently mutated gene in our patient cohort, as in most previous reports, different mutation distribution among the other genes studied motivates the use of a next-generation sequencing gene panel including the possible responsible genes.

Wiedemann-Steiner syndrome (WDSTS) is a rare autosomal dominant disorder with a variable clinical phenotype including synophrys, hypertelorism, thick eyebrows, long eyelashes, wide nasal bridge, long philtrum, hypertrichosis, growth retardation, and intellectual disability. Cornelia de Lange syndrome (CdLS) is a rare disease characterized by synophrys, long eyelashes, limb abnormalities, generalized hirsutism, growth retardation, and intellectual disability. In both WDSTS and CdLS, the malformations are due to transcriptome disturbance caused by defects in the genes encoding the components of chromatin regulation and transcription process. The overlapping features in these two syndromes may complicate the original diagnosis of a patient. Here, we report on a Wiedemann-Steiner patient found to have a de novo pathogenic KMT2Avariation who had been clinically suspected as CdLS. We suggest that targeted next-generation sequencing is a feasible tool for the precise diagnosis of patients who have phenotypically and clinically overlapping features of CdLS and WDSTS.

Inflammatory bowel disease is a group of chronic inflammatory conditions affecting gastrointestinal tract. Lots of genes have been identified resulting in susceptibility to inflammatory bowel disease. Any polymorphism leading to functional modifications in tyrosine kinase-2 may precipitate excessive immune response in the intestinal mucosa. The aim of our study is to investigate the involvement of tyrosine kinase-2 polymorphisms in the patients with inflammatory bowel disease in Turkish population.

A novel systematic procedure referred to as "SYMPES" to model speech signals is introduced. The structure of SYMPES is based on the creation of the so-called predefined "signatureand envelope" sets. These sets are speaker and language independent. Once the speech signals are divided into frames with selected lengths, then each frame sequenceis reconstructed by means of the mathematical form. In this representation,is called the gain factor,andare properly assigned from the predefined signature and envelope sets, respectively. Examples are given to exhibit the implementation of SYMPES. It is shown that for the same compression ratio or better, SYMPES yields considerably better speech quality over the commercially available coders such as G.726 (ADPCM) at 16 kbps and voice excited LPC-10E (FS1015) atkbps.

A novel method is proposed to model ECG signals by means of "predefined signature and envelope vector sets (PSEVS)." On a frame basis, an ECG signal is reconstructed by multiplying three model parameters, namely, predefined signature vector," "predefined envelope vector," and frame-scaling coefficient (FSC). All the PSVs and PEVs are labeled and stored in their respective sets to describe the signal in the reconstruction process. In this case, an ECG signal frame is modeled by means of the members of these sets labeled with indicesandand the frame-scaling coefficient, in the least mean square sense. The proposed method is assessed through the use of percentage root-mean-square difference (PRD) and visual inspection measures. Assessment results reveal that the proposed method provides significant data compression ratio (CR) with low-level PRD values while preserving diagnostic information. This fact significantly reduces the bandwidth of communication in telediagnosis operations.

The objective of this study was to report the first case of prenatal diagnosis of the fetal 20p13 microdeletion syndrome in the literature.

• Increasing biometric identification performance using the fusion of ECG and speech. • Newly developed method for removing spikes and inconsistencies in ECG signals. • Contains robust unauthorized user rejection option. • Combines the verification and identification algorithms into a single system. • An alternative approach to the Universal Background Model. In this research work, we propose a one-dimensional Convolutional Neural Network (CNN) based biometric identification system that combines speech and ECG modalities. The aim is to find an effective identification strategy while enhancing both the confidence and the performance of the system. In our first approach, we have developed a voting-based ECG and speech fusion system to improve the overall performance compared to the conventional methods. In the second approach, we have developed a robust rejection algorithm to prevent unauthorized access to the fusion system. We also presented a newly developed ECG spike and inconsistent beats removal algorithm to detect and eliminate the problems caused by portable fingertip ECG devices and patient movements. Furthermore, we have achieved a system that can work with only one authorized user by adding a Universal Background Model to our algorithm. In the first approach, the proposed fusion system achieved a 100% accuracy rate for 90 people by taking the average of 3-fold cross-validation. In the second approach, by using 90 people as genuine classes and 26 people as imposter classes, the proposed system achieved 92% accuracy in identifying genuine classes and 96% accuracy in rejecting imposter classes. [ABSTRACT FROM AUTHOR]