Case report: genetic analysis of a novel frameshift mutation in FMR1 gene in a Chinese family.

Fragile X syndrome (FXS) [OMIM 300624] is a common X-linked inherited syndrome with an incidence only second to that of trisomy 21. More than 95% of fragile X syndrome is caused by reduced or absent fragile X intellectual disability protein 1 (FMRP) synthesis due to dynamic mutation expansion of the CGG triplet repeat in the 5'UTR and abnormal methylation of the FMR1 (fragile X messenger ribonucleoprotein 1) gene [OMIM 309550]. Less than 5% of cases are caused by abnormal function of the FMRP due to point mutations or deletions in the FMR1 gene. In a proband with clinical suspicion of FXS and no CGG duplication, we found the presence of c.585_586del (p.Lys195AsnfsTer8) in exon 7 of the FMR1 gene using whole exome sequencing (WES). This variant resulted in frameshift and a premature stop codon after 8 aberrant amino acids. This variant is a novel pathogenic mutation, as determined by pedigree analysis, which has not been reported in any database or literature.

Investigating the impact of vulnerability datasets on deep learning-based vulnerability detectors.

Software vulnerabilities have led to system attacks and data leakage incidents, and software vulnerabilities have gradually attracted attention. Vulnerability detection had become an important research direction. In recent years, Deep Learning (DL)-based methods had been applied to vulnerability detection. The DL-based method does not need to define features manually and achieves low false negatives and false positives. DL-based vulnerability detectors rely on vulnerability datasets. Recent studies found that DL-based vulnerability detectors have different effects on different vulnerability datasets. They also found that the authenticity, imbalance, and repetition rate of vulnerability datasets affect the effectiveness of DL-based vulnerability detectors. However, the existing research only did simple statistics, did not characterize vulnerability datasets, and did not systematically study the impact of vulnerability datasets on DL-based vulnerability detectors. In order to solve the above problems, we propose methods to characterize sample similarity and code features. We use sample granularity, sample similarity, and code features to characterize vulnerability datasets. Then, we analyze the correlation between the characteristics of vulnerability datasets and the results of DL-based vulnerability detectors. Finally, we systematically study the impact of vulnerability datasets on DL-based vulnerability detectors from sample granularity, sample similarity, and code features. We have the following insights for the impact of vulnerability datasets on DL-based vulnerability detectors: (1) Fine-grained samples are conducive to detecting vulnerabilities. (2) Vulnerability datasets with lower inter-class similarity, higher intra-class similarity, and simple structure help detect vulnerabilities in the original test set. (3) Vulnerability datasets with higher inter-class similarity, lower intra-class similarity, and complex structure can better detect vulnerabilities in other datasets.

[Emission Inventory and Emission Factors of Volatile Organic Compounds (VOCs) from Architectural Adhesives].

Architectural decoration is an important anthropogenic emission source of VOCs in China, and there are few studies on the emission of VOCs from architectural adhesives. In this study, the VOCs content level and emission factors of various architectural adhesives were measured and then, a VOC emission inventory of architectural adhesives in China from 2013 to 2017 was established by a top-down emission factor method. Results showed that the comprehensive VOCs emission factor of architectural adhesives was 97.0 kg·t-1, of which 543 kg·t-1 was from solvent-based architectural adhesives, 45 kg·t-1 was from water-based architectural adhesives, and 63 kg·t-1 was from bulk architectural adhesives. The VOCs emissions from architectural adhesives were 165 kt, 181 kt, 188 kt, 201 kt, and 219 kt from 2013 to 2017 in China. The contribution of VOCs emission of various disparate architectural adhesives was 25.5%, 23.6%, and 50.9% for water-based, bulk, and solvent-based types, respectively. Shandong, Jiangsu, Zhejiang, Sichuan, Guangdong, Henan, Yunnan, and Fujian provinces contributed significant amounts, with a total emission of 120 kt in 2017, accounting for nearly 55% of the total VOCs emission for architectural adhesives.

Case Report: Prenatal Diagnosis of a Fetus With Harlequin Ichthyosis Identifies Novel Compound Heterozygous Variants: A Case Report.

BACKGROUND: Harlequin ichthyosis (HI) is the most severe form of the keratinizing disorders, and it is characterized by whole-body hard stratum corneum. ABCA12 has been identified as the major disease-causing gene of HI. METHODS: A case of HI was prenatally diagnosed by ultrasonography and genetic tests. The fetus had been found with dentofacial deformity and profound thickening of the palm and plantar soft tissues. Chromosomal microarray analysis (CMA) and whole exome sequencing (WES) were then performed on the amniotic fluid to identify germline pathogenic variants for the fetus. Candidate variants were verified by Sanger sequencing. RESULTS: Compound heterozygous frameshift variants (p.Q719QfsX21; p.F2286LfsX6) of ABCA12 were identified for the fetus, suggesting the former variants were maternally inherited and the latter paternally inherited. The fetus was terminated. CONCLUSION: A prenatal molecular diagnosis is an important approach for the prevention of HI. In the study, we provided a successful case of genetic counseling for a family with an HI baby.

[Raw Materials and End Treatment-based Emission Factors for Volatile Organic Compounds (VOCs) from Typical Solvent Use Sources].

A database of refined raw materials and end treatment-based VOCs emission factors for typical solvent use sources was developed for the Pearl River Delta. For this, the impact of composition and the content of raw materials, production process, and comprehensive end treatment on the emission of VOCs was analyzed. The solvent use sources included printing, furniture manufacturing, and electronic component and equipment manufacturing. The results showed that the main VOCs in the raw materials used in printing were ethyl acetate, propyl acetate, isopropanol, propanol, and ethanol, which contributed 60%-80% to the total amount of VOCs. Ethyl acetate and butyl acetate were the main oxygenated VOCs (OVOCs) from the raw materials used in furniture manufacturing, contributing 45%-65% of the total. The main VOCs from the raw materials used in electronic component and equipment manufacturing were OVOCs such as alcohols, ethers and phenols, BTEX, and halohydrocarbons. The uncontrolled and controlled emission factors for VOCs from printing were 415.2 kg·t-1 and 184.3 kg·t-1, respectively. Of these, solvent-based raw materials accounted for 704.9 kg·t-1 and 200.1 kg·t-1, water-based raw materials accounted for 325.6 kg·t-1 and 230.3 kg·t-1, UV raw materials accounted for 197.0 kg·t-1 and 129.0 kg·t-1, and plant-based raw materials accounted for 89.0 kg·t-1 and 89.0 kg·t-1, respectively. The uncontrolled and controlled emission factors for VOCs from furniture manufacturing were 379.0 kg·t-1 and 290.2 kg·t-1, respectively. Of these, solvent-based raw materials accounted for 603.0 kg·t-1 and 448.5 kg·t-1, water-based raw materials accounted for 80.0 kg·t-1 and 80.0 kg·t-1, and powder raw materials accounted for 230.0 kg·t-1 and 184.0 kg·t-1, respectively. In electronic component and equipment manufacturing, the uncontrolled and controlled emission factors (unit:kg·million-1) for VOCs from AC ceramic capacitors, CC ceramic capacitors, varistors, and aluminum electrolytic capacitors were 59.7 and 40.8, 394.1 and 269.6, 282.4 and 193.2, and 1.2 and 1.0, respectively. The uncontrolled and controlled emission factors for VOCs from the manufacturing of continuous terminals, enameled wire, and printed circuit boards were 56.3 kg·t-1 and 42.8 kg·t-1, 87.2 kg·t-1 and 28.3 kg·t-1, and 26.4 kg·(100 m2)-1 and 11.6 kg·(100 m2)-1, respectively.

Paternal Low-Level Mosaicism-Caused SATB2-Associated Syndrome.

Mutations of SATB2 (OMIM#608148) gene at 2q33.1 have been associated with the autosomal dominant SATB2-associated syndrome (SAS), which is still short of comprehensive diagnosis technologies for small deletions and low-level mosaicism. In this Chinese Han family, single nucleotide polymorphism array identified a 4.9-kb deletion in the SATB2 gene in two consecutive siblings exhibiting obvious developmental delay and dental abnormalities but failed to find so in their parents. Prenatal diagnosis revealed that their third child carried the same deletion in SATB2 and the pregnancy was terminated. To determine the genetic causes behind the inheritance of SATB2 deletion, gap-PCR was performed on peripheral blood-derived genomic DNA of the family and semen-derived DNA from the father. Gap-PCR that revealed the deletions in the two affected siblings were inherited from the father, while the less intense mutant band indicated the mosaicism of this mutation in the father. The deletion was 3,013 bp in size, spanning from chr2: 200,191,313-200,194,324 (hg19), and covering the entire exon 9 and part of intron 8 and 9 sequences. Droplet digital PCR demonstrated mosaicism percentage of 13.2% and 16.7% in peripheral blood-derived genomic DNA and semen-derived DNA of the father, respectively. Hereby, we describe a family of special AT-rich sequence-binding protein 2-associated syndrome caused by paternal low-level mosaicism and provide effective diagnostic technologies for intragenic deletions.

[Phenotypic and genetic analysis of a sibpair with partial deletion of SATB2 gene caused by 2q33.1 microdeletion].

OBJECTIVE: To analyze the genotype and phenotype of a sibpair with partial deletion of SATB2 gene caused by 2q33.1 microdeletion. METHODS: Both children have featured mental retardation and development delay, and were subjected to karyotyping, single nucleotide microarray (SNP array) and real-time fluorescence quantitative PCR analysis. Karyotyping and SNP Array analysis were also carried out on their parents to verify the origin of mutation. RESULTS: Both sibs had a normal karyotype. SNP array showed that sib 1 had arr[hg19]2q33.1(200 192 328 - 200 197 269)×1 (4.9 kb), 2q35 (218 105 663 - 218 816 675)×3 (711 kb), while sib 2 had arr[hg19]2q33.1(200 192 328 - 200 197 269)×1 (4.9 kb), 2q35 (218 105 663-218 810 908)×3 (705.2 kb). The deletion has partially overlapped with that of 2q33.1 microdeletion syndrome and involved part of the SATB2 gene. The result of real-time fluorescence quantitative PCR assay was consistent with that of SNP assay. The duplication has originated from their father and has not been associated with any disease phenotypen. CONCLUSION: Both sibs have carried partial deletion of SATB2 gene and had similar clinical phenotypes. Haploinsufficiency of such gene probably underlies the clinical manifestations in both patients.

[Application of BACs-on-Beads and karyotyping for the prenatal diagnosis of 1371 pregnant women with a high risk].

OBJECTIVE: To assess the value of combined BACs-on-BeadsTM (BoBs) and chromosomal karyotyping for the diagnosis of women with high-risk pregnancy. METHODS: For 1371 women with singleton pregnancy and various indications for prenatal diagnosis, karyotyping and BoBs were simultaneously applied on their amnionic fluid samples. RESULTS: In total 23 cases of trisomy 21, 11 cases of trisomy 18, 5 cases of sex chromosome aneuploidies, 6 cases of microdeletions/microduplications, 2 cases of chimeric chromosomes and 1 case of structural chromosomal abnormality were detected by the BoBs assay, among which the 6 microdeletions/microduplications were not detected by karyotyping. Karyotyping analysis has identified an extra yield of 19 chromosomal abnormalities and 34 chromosomal polymorphisms. CONCLUSION: Combined use of BoBs and chromosomal karyotyping can improve the detection rate of fetal chromosomal abnormalities including microdeletions/microduplications, which should find a wider use in the clinics.

Risk factors and management of gestational diabetes.

Gestational diabetes mellitus (GDM) is considered to be a typical condition of glucose intolerance in which a woman previously undiagnosed with diabetes exhibits high levels of blood glucose during the third trimester of pregnancy. It can hence be defined as any degree of intolerance to glucose with its first recognition only during the pregnancy. Approximately 7 % of all cases of pregnancy are found to be variedly complicated with GDM and this result in more than 200,000 cases annually. In US only, GDM has been found to complicate about 7-14 % cases annually, and the trend seems to have increased by 35-100 % in the recent years. A history of GDM can be considered to be one of the sturdiest risk factors concerning the development of type 2 diabetes. Among women who have a history of GDM, the risk of developing classical type 2 diabetes usually ranges from 20 to 50 %. Evidences collected from various efficacy trials suggest that lifestyle interventions like weight management can modulate and prevent type 2 diabetes in at-risk individuals. The cornerstone of GDM management is glycemic control, and hence, it is attributed to be the main focus of attention for the therapy. In this review, we have tried to highlight the various risk factors associated with GDM along with the available therapeutic options in the treatment and management of the disease.