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Purpose This study aims to describe the phenotypes and identify pathogenic mutations in Chinese patients who have congenital cataracts associated with other ocular abnormalities. Methods Eleven patients from four unrelated Chinese families plus two simplex cases were enrolled in this study. Detailed ophthalmic examinations were performed. DNA samples were isolated from peripheral blood collected from the patients. Next-generation sequencing of known ocular genes was applied to the proband of each family and two simplex cases to find pathogenic variances. PCR and Sanger sequencing were conducted for validation and segregation tests. Results All 13 patients had congenital cataracts, and other ocular abnormalities were found in some cases. Microcornea was found in 12 subjects, and ocular coloboma was observed in five. Various types of coloboma, including iris, choroid, macular, and optic disc, were described. Five mutations in crystallin genes were identified. Four of the mutations are novel: CRYBB1: p.(Arg230Cys), CRYBB2: p.(Gly149Val), CRYGC: p.(Met44CysfsTer59), and CRYGC: p.(Tyr144Ter). One mutation was reported previously: CRYAA: p.(Arg21Trp). Conclusions We examined a cohort of Chinese patients with congenital cataracts and studied the phenotypes and genotypes. Extralenticular abnormalities, such as microcornea and ocular coloboma, can also be found in patients with congenital cataracts. The phenotype of congenital cataracts associated with macular and optic disc coloboma was reported for the first time in this study. Four novel mutations and one previously reported mutation were identified. These data expand the mutation spectrum in crystallin genes and enhance our understanding of the phenotypes of congenital cataracts.

The scheduling and operation of power system becomes prominently complex and uncertain, especially with the penetration of distributed power. Load forecasting matters to the effective operation of power system. This paper proposes a novel deep learning framework to forecast the short-term grid load. First, the load data is processed by Box-Cox transformation, and two parameters (electricity price and temperature) are investigated. Then, to quantify the tail-dependence of power load on the two parameters, parametric Copula models are fitted and the threshold of peak load are computed. Next, a deep belief network is built to forecast the hourly load of the power grid. One year grid load data collected from an urbanized area in Texas, United States is utilized in the case studies. Short-term load forecasting are examined in four seasons independently. Day-ahead and week-ahead load forecasting experiments are conducted in each season using the proposed framework. The proposed framework is compared with classical neural networks, support vector regression machine, extreme learning machine, and classical deep belief networks. The load forecasting performances are assessed by mean absolute percentage error, root mean square error, and hit rate. Computational results confirm the effectiveness of the proposed data-driven deep learning framework. The prediction accuracies of both day-ahead forecasting and week-ahead forecasting demonstrate that the proposed framework outperforms the tested algorithms., 8 pages, 8 figures

Stargardt macular dystrophy (STGD) results in early central vision loss. We sought to explain the genetic cause of STGD in a cohort of 88 patients from three different cultural backgrounds.Next-generation sequencing using a novel capture panel was used to search for disease-causing mutations. Patients with undetermined causes were clinically reexamined and tested for copy-number variations as well as intronic mutations.We determined the cause of disease in 67% of our patients. Our analysis identified 35 novel ABCA4 alleles. Eleven patients had mutations in genes not previously reported to cause STGD. Finally, 45% of our patients with unsolved causes had single deleterious mutations in ABCA4, a recessive disease gene. No likely pathogenic copy-number variations were identified.This study expands our knowledge of STGD by identifying dozens of novel alleles that cause the disease. The frequency of single mutations in ABCA4 among STGD patients is higher than that among controls, indicating that these mutations contribute to disease. Disease in 11 patients was explained by mutations outside ABCA4, underlining the need to genotype all retinal disease genes to maximize genetic diagnostic rates. Few ABCA4 mutations were observed in our French Canadian patients. This population may contain an unidentified founder mutation. Our results indicate that copy-number variations are unlikely to be a major cause of STGD.

Purpose Alström syndrome (AS) is a rare monogenic autosomal recessively inherited disorder characterized by cone rod dystrophy and multiple organ dysfunction. Mutations in the Alström syndrome 1 (ALMS1) gene have been found to be causative for AS. The purpose of this study was to identify ALMS1 mutations and to assess the clinical features of Chinese patients with AS. Methods Detailed ocular and laboratory examinations were performed. Peripheral blood samples were collected from patients and their parents. Genomic DNA was extracted with a Qiagen kit. Exons and exon/intron junctions of ALMS1 were amplified with polymerase chain reaction (PCR) and screened for mutations with Sanger sequencing. The results were compared with the ALMS1 transcript to exclude polymorphisms and confirm pathogenic mutations. Results Seven patients from five unrelated non-consanguineous families were diagnosed with AS. All patients had cone rod dystrophy with impaired visual acuity, photophobia, and nystagmus. Other clinical features, including sensorineural hearing loss, truncal obesity, insulin resistance, type 2 diabetes mellitus, renal and hepatic dysfunction, hyperlipidemia, hypothyroidism, mental retardation, acanthosis nigricans, and scoliosis, were present. Sequencing revealed two novel mutations, p.N3150Kfs2X and p.V3154Xfs, in patient 1; one novel mutation, p.N3672Ifs11X, and one previously reported nonsense mutation, p.R3703X, in patient 2; novel mutations p.S2479X and p.R3611Efs7X in patient 3; one novel homozygous mutation, p.S695X, in patients 4 and 5; and two novel mutations, p.H688HfsX and p.Q3147Qfs2X, in patients 6 and 7. These mutations were not present in 100 unrelated healthy Chinese control subjects. The patients’ parents were heterozygous carriers of the mutant allele. Conclusions Seven Chinese patients with AS showed typical ophthalmic features and multiple organ dysfunction. Novel loss of function mutations in the ALMS1 gene are the underlying genetic defects.