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Congenital hydrocephalus (CH) is a severe birth defect, and genetics components is an important etiology. Whole‐exome sequencing (WES) has been proven to be a feasible approach for prenatal diagnosis of CH. In this study, we carried out WES on three fetuses with cerebral ventriculomegaly. After bioinformation analysis and data filtering, three compound variants, c.919C>T(p.Arg307Ter)/c.1100del(p.Phe369fs) in FKTN, c.1449_1450insACAACG/c.1490G>C(p.Arg497Pro) in POMGNT1, and c.2690+1G>A/c.1447C>T(p.Arg483Cys) in LAMB1 were detected in the three fetuses. All the six variants were classified as likely pathogenic or pathogenic in accordance with the American College of Medical Genetics and Genomics‐Association for Molecular Pathology guidelines. This study provides support for the potential of WES for the accurate prenatal diagnosis of fetal hydrocephalus and further demonstrated the genetic heterogeneity in patients with CH. The novel variants (c.1449_1450insACAACG and c.1490G>C in POMGNT1, c.2690+1G>A in LAMB1) expanded the gene mutational spectrum of CH and contributes to genetics counseling and pregnancy management. [ABSTRACT FROM AUTHOR]

Peanuts are highly susceptible to contamination by aflatoxins, posing a significant threat to human health. This study aims to enhance the accuracy of pixel-level aflatoxin detection in hyperspectral images using an optimized deep learning method. This study developed a CNN-BiLSTM fusion model optimized by the Multi-Verse Optimizer (MVO) algorithm, specifically designed to detect aflatoxins with high precision. The optimized CNN-BiLSTM model was fine-tuned using aflatoxin spectral data at varying concentrations. The results indicate that the fine-tuned MVO-CNN-BiLSTM model achieved the best performance, with a validation accuracy of 94.92 % and a recall rate of 95.59 %. The accuracy of this model is 6.93 % and 3.6 % higher than machine learning methods such as SVM and AdaBoost, respectively. Additionally, it is 4.18 % and 3.08 % higher than deep learning methods such as CNN and the CNN-LSTM fusion model, respectively. This method enhances pixel-level aflatoxin detection accuracy, supporting the development of online detection devices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: To determine the carrier rate of Fragile X mental retardation 1 gene (FMR1) mutants in women with a history of adverse pregnancy or childbirth, and to provide prenatal diagnosis for the carriers., Methods: Peripheral blood samples were collected from women with a history of adverse pregnancy or childbirth, and the FMR1 gene cytosine-guanine-guanine repeat number (CGG)n was determined by triple-repeat primer polymerase chain reaction (TP-PCR) combined with capillary electrophoresis. Prenatal diagnosis was provided for the carriers during pregnancy., Results: Among 819 samples, 9 gray zone repeats carriers and 10 premutation carriers were detected, which gave a prevalence of 1 in 91 and 1 in 82, respectively, with a total prevalence of 1 in 43. Prenatal diagnosis was provided during 7 pregnancies for 6 carriers. A female fetus with premutation (n = 30/57) and an affected male fetus with full mutation (n = 336) were detected., Conclusion: FMR1 gene testing in women with a history of adverse pregnancy or childbirth can facilitate genetic counseling and reproductive guidance for carriers of gray zone repeats and premutations. Prenatal diagnosis for carriers of premutation can facilitate reduction of the birth of children with fragile X syndrome.

Objective: To apply single nucleotide polymorphism array (SNP-array) for the diagnosis of Williams-Beuren syndrome (WBS) in a patient., Methods: Chromosome G-banding and SNP-array were used to analyze a girl featuring mental retardation., Results: The karyotypes of the child and her parents were all normal, but SNP-array showed a 1.9 Mb deletion at 7q11.23 in the patient. The same deletion was not found in her parents., Conclusion: The mental retardation and special facies of the girl were probably due to the 7q11.23 microdeletion. SNP-array has an important value for the diagnosis of mental retardation.