Spectrum of GJB2 mutations in Turkey comprises both Caucasian and Oriental variants: roles of parental consanguinity and assortative mating

Considerable differences exist for the spectrum of GJB2 mutations in different populations. Screening for the c.35delG mutation in 256 independent probands, 154 multiplex (familial) and 102 simplex (sporadic), coming from different regions of Turkey revealed 37 (14.5%) homozygotes. The allele frequency of c.35delG ranged from 5% to 53% in different cities. Parental consanguinity was noted in 34% of c.35delG homozygotes, yet it was 55% in c.35delG negatives (p=0.034). Further screening for GJB2 mutations in multiplex families demonstrated the presence of c.167delT and L90P mutations as well as a novel complex mutation, c.236_239delTGCAinsAGATCCG, in single alleles, leading to compound heterozygosity with c.35delG. The homozygous E120del mutation was found in another case. The V27I polymorphism was detected in five alleles, one of which was associated with the E114G change. Assortative mating was a significant factor predicting to detect biallelic mutations in the GJB2 gene. These results confirm the overwhelming majority of c.35delG in the Turkish deaf individuals as well as the presence of other changes detected in Caucasian and Asian populations

Vulnerability Prediction from Source Code Using Machine Learning

As the role of information and communication technologies gradually increases in our lives, software security becomes a major issue to provide protection against malicious attempts and to avoid ending up with noncompensable damages to the system. With the advent of data-driven techniques, there is now a growing interest in how to leverage machine learning (ML) as a software assurance method to build trustworthy software systems. In this study, we examine how to predict software vulnerabilities from source code by employing ML prior to their release. To this end, we develop a source code representation method that enables us to perform intelligent analysis on the Abstract Syntax Tree (AST) form of source code and then investigate whether ML can distinguish vulnerable and nonvulnerable code fragments. To make a comprehensive performance evaluation, we use a public dataset that contains a large amount of function-level real source code parts mined from open-source projects and carefully labeled according to the type of vulnerability if they have any.We show the effectiveness of our proposed method for vulnerability prediction from source code by carrying out exhaustive and realistic experiments under different regimes in comparison with state-of-art methods

TRANSPLANTATION IN FSGS: A MULTICENTRIC STUDY FROM TURKEY

WOS: 000443998400450

A rare cause of urolithiasis in an infant: Answers

koyun, mustafa/0000-0002-6707-1001WOS:000608672300009PubMed: 33459934[No Abstract Available

PRIMARY HYPEROXALURIA TYPE 1 PROGRESSING TO END-STAGE RENAL FAILURE AT INFANCY

[No Abstract Available

A rare cause of urolithiasis in an infant: Questions

koyun, mustafa/0000-0002-6707-1001WOS:000608672300001PubMed: 33459935[No Abstract Available

SoK:Investigation of security and functional safety in industrial IoT

There has been an increasing popularity of industrial usage of Internet of Things (IoT) technologies in parallel to advancements in connectivity and automation. Security vulnerabilities in industrial systems, which are considered less likely to be exploited in conventional closed settings, have now started to be a major concern with Industrial IoT. One of the critical components of any industrial control system turning into a target for attackers is functional safety. This vital function is not originally designed to provide protection against malicious intentional parties but only accidents and errors. In this paper, we explore a generic IoT-based smart manufacturing use-case from a combined perspective of security and functional safety, which are indeed tightly correlated. Our main contribution is the presentation of a taxonomy of threats targeting directly the critical safety function in industrial IoT applications. Besides, based on this taxonomy, we identified particular attack scenarios that might have severe impact on physical assets like manufacturing equipment, even human life and cyber-assets like availability of Industrial IoT application. Finally, we recommend some solutions to mitigate such attacks based mainly on industry standards and advanced security features of mobile communication technologies

CLINICAL COURSE OF C3 GLOMERULOPATHY IN TURKISH CHILDREN: A MULTICENTER STUDY

WOS: 000443998400333