New Ocular Findings in a Patient with a Novel Pathogenic Variant in the FBXO11 Gene

Intellectual developmental disorder with dysmorphic facies and behavioral abnormalities (IDDFBA) is a recently described autosomal dominant entity caused by pathogenic variants, mostly de novo, in the FBXO11 gene. It presents in the first years of life with highly variable clinical manifestations. The main features of IDDFBA include borderline-to-severe intellectual disability, behavioral problems, hypotonia, facial dysmorphisms, minor skeletal abnormalities, and recurrent infections. Although eye problems, such as refractive errors, eye misalignment and minor visual changes, have been described in about 48% of patients, a major ocular defect, namely, bilateral optic nerve hypoplasia, has been reported in the literature only once. We report an 8-year-old boy with a novel de novo pathogenic variant in FBXO11 gene (NM_001190274.1: c.1166dup, p.Cys390Metfs∗3) and a complex ophthalmological phenotype, consisting of right microphthalmia, very shallow anterior chamber, and persistent pupillary membrane, right dense nuclear cataract, bilateral optic nerve hypoplasia, and bilateral horizontal manifest nystagmus.info:eu-repo/semantics/publishedVersio

Extending the applicability of the dose addition model to the assessment of chemical mixtures of partial agonists by using a novel toxic unit extrapolation method

This article has been made available through the Brunel Open Access Publishing Fund.Dose addition, a commonly used concept in toxicology for the prediction of chemical mixture effects, cannot readily be applied to mixtures of partial agonists with differing maximal effects. Due to its mathematical features, effect levels that exceed the maximal effect of the least efficacious compound present in the mixture, cannot be calculated. This poses problems when dealing with mixtures likely to be encountered in realistic assessment situations where chemicals often show differing maximal effects. To overcome this limitation, we developed a pragmatic solution that extrapolates the toxic units of partial agonists to effect levels beyond their maximal efficacy. We extrapolated different additivity expectations that reflect theoretically possible extremes and validated this approach with a mixture of 21 estrogenic chemicals in the E-Screen. This assay measures the proliferation of human epithelial breast cancers. We found that the dose-response curves of the estrogenic agents exhibited widely varying shapes, slopes and maximal effects, which made it necessary to extrapolate mixture responses above 14% proliferation. Our toxic unit extrapolation approach predicted all mixture responses accurately. It extends the applicability of dose addition to combinations of agents with differing saturating effects and removes an important bottleneck that has severely hampered the use of dose addition in the past. © 2014 Scholze et al

Polyvalent horse F(Ab`)2 snake antivenom: Development of process to produce polyvalent horse F(Ab`)2 antibodies anti-african snake venom

A method to obtain polyvalent anti-Bitis and polyvalent-anti-Naja antibodies was developed by immunizing horses with B. arietans, B. nasicornis, B. rhinoceros, N. melanoleuca and N. mossambicacrude venoms. Antibody production was followed by the ELISA method during the immunization procedure. Once the desired anti-venom antibody titers were attained, horses were bled and the immunoglobulins were separated from the sera by (NH4)2SO4 precipitation, cleaved with pepsin and filtered through a 30 kDa ultrafiltration membrane. F(ab´)2 fragments were further purified by Q-Fast Flow chromatography, concentrated by molecular ultrafiltration and sterilized by filtration through 0.22 m membranes. The resulting F(ab´)2 preparations were rich in intact L and in pieces of H IgG(T) chains, as demonstrated by electrophoresis and Western blot and exhibited high antibody titers, as assayed by the ELISA method. In addition, the preparations possess a significant capacity to neutralize the lethality of venoms, as estimated by ED50 determination in mouse assay and are free of toxic substances, pyrogen and bacterial or fungal contaminations

Using deep learning for ordinal classification of mobile marketing user conversion

In this paper, we explore Deep Multilayer Perceptrons (MLP) to perform an ordinal classification of mobile marketing conversion rate (CVR), allowing to measure the value of product sales when an user clicks an ad. As a case study, we consider big data provided by a global mobile marketing company. Several experiments were held, considering a rolling window validation, different datasets, learning methods and performance measures. Overall, competitive results were achieved by an online deep learning model, which is capable of producing real-time predictions.This article is a result of the project NORTE-01-0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by Funda¸c˜ao para a Ciˆencia e Tecnologia (FCT) within the Project Scope: UID/CEC/00319/201