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The EFSA 'Guidance on tiered risk assessment for edge-of-field surface waters' underscores the importance of in silico models to support the pesticide risk assessment. The aim of this work was to use in silico models starting from an available, structured and harmonized pesticide dataset that was developed for different purposes, in order to stimulate the use of QSAR models for risk assessment. The present work focuses on the development of a set of in silico models, developed to predict the aquatic toxicity of heterogeneous pesticides with incomplete/unknown toxic behavior in the water compartment. The generated models have good fitting performances (R2 0.75-0.99), they are internally robust (Q2loo 0.66-0.98) and can handle up to 30% of perturbation of the training set (Q2 lmo 0.64-0.98). The absence of chance correlation was guaranteed by low values of R2 calculated on scrambled responses (R2 Yscr 0.11-0.38). Different statistical parameters were used to quantify the external predictivity of the models (CCCext 0.73-0.91, Q2 ext-Fn 0.53-0.96). The results indicate that all the best models are predictive when applied to chemicals not involved in the models development. In addition, all models have similar accuracy both in fitting and in prediction and this represents a good degree of generalization. These models may be useful to support the risk assessment procedure when experimental data for key species are missing or to create prioritization lists for the general a priori assessment of the potential toxicity of existing and new pesticides which fall in the applicability domain. Spinal muscular atrophy (SMA) is a leading genetic cause of infant death, influenced by the copy number of two highly-homologous genes SMN1 and SMN2. Although exome-seq is widely applied for genetic testing, SMA diagnosis and carrier screening have not been incorporated in routine exome-seq data analysis and lack of evaluation in clinical applications. We established a workflow for SMN gene copy number analysis based on unique-mapped reads on exon 7 of SMN genes and the control region. The workflow was retrospectively applied in the NICU cohort and validated with multiple ligation-dependent probe amplification. The predictions of our method are completely consistent with benchmark dataset (n=104). The retrospective analysis in the NICU cohort detected and confirmed eight SMN1 homozygous-deletions and 60 carriers (n=3,734). With multiple ligation-dependent probe amplification confirmation, the receiver operating characteristic curve analysis result showed the area under curve of 100% and 97.8%, respectively, in predicting SMN1 homozygous deletion and heterozygous deletion event, and 99.2% and 96.2%, respectively, in SMN2 deletion and duplication event. The results demonstrated favorable ability in both SMN1 and SMN2 copy number status prediction based on real clinical exome-seq data. This study provides a precise and portable workflow for both SMN1 and SMN2 copy number analysis based on exome-seq, assisting SMA diagnosing, carrier screening, and disease severity warning in clinical application. Testing asymptomatic individuals for unsuspected conditions is not new to the medical and public health communities. Protocols to develop screening tests are well-established. However, the application of screening principles to inherited diseases presents unique challenges. Unlike most screening tests, the natural history and disease prevalence of most rare inherited diseases in an unselected population are unknown. It is difficult or impossible to obtain a "truth set" cohort for clinical validation studies. As a result, it is not possible to accurately calculate clinical positive and negative predictive values for "likely pathogenic" variants, which are commonly returned in genetic screening assays. In addition, many of the genetic conditions included in screening panels do not have clinical confirmatory tests. All of these elements are typically required to justify the development of a screening test, according to the World Health Organization screening principles. Nevertheless, as the cost of DNA sequencing continues to fall, more individuals are opting to undergo genomic testing in the absence of a clinical indication. Despite the challenges, reasonable estimates can be deduced and used to inform test design strategies. Here, we review basic test design principles and apply them to genetic screening. When a potential disease-causing variant is detected in a proband, parental testing is used to determine the mode of inheritance. This study demonstrates that next-generation sequencing (NGS) is uniquely well suited for parental testing, in particular because of its ability to detect clinically relevant germline mosaicism. Parental variant testing by NGS was performed in a clinical laboratory for 1 year. The detection of mosaicism by NGS was compared with its detection by Sanger sequencing. Eight cases of previously unrevealed mosaicism were detected by NGS across eight different genes. Mosaic variants were differentiated from sequencing noise using custom bioinformatics analyses in combination with familial inheritance data and complementary Sanger sequencing. Sanger sequencing detected mosaic variants with allele fractions ≥8% by NGS, but could not detect mosaic variants below that level. Detection of germline mosaicism by NGS is invaluable to parents, providing a more accurate recurrence risk that can alter decisions on family planning and pregnancy management. Because NGS can also confirm parentage and increase scalability, it simultaneously streamlines and strengthens the variant curation process. [https://www.selleckchem.com/products/folinic-acid.html Folinic] These features make NGS the ideal method for parental testing, superior even to Sanger sequencing for most genomic loci. One of the most perplexing questions regarding the current COVID-19 coronavirus epidemic is the discrepancy between the severity of cases observed in the Hubei province of China and those occurring elsewhere in the world. One possible answer is antibody dependent enhancement (ADE) of SARS-CoV-2 due to prior exposure to other coronaviruses. ADE modulates the immune response and can elicit sustained inflammation, lymphopenia, and/or cytokine storm, one or all of which have been documented in severe cases and deaths. ADE also requires prior exposure to similar antigenic epitopes, presumably circulating in local viruses, making it a possible explanation for the observed geographic limitation of severe cases and deaths.